This paper represents the scheduling process in furniture manufacturing unit. It gives the fuzzy logic application in flexible manufacturing system. Flexible manufacturing systems are production system in furniture manufacturing unit. FMS consist of same multipurpose numerically controlled machines. Here in this project the scheduling has been done in FMS by using fuzzy logic tool in Matlab software. The fuzzy logic based scheduling model in this paper will deals with the job and best alternative route selection with multi-criteria of machine. Here two criteria for job and sequencing and routing with rules. This model is applicable to the scheduling of any manufacturing industry.
Modified heuristic time deviation Technique for job sequencing and Computatio...ijcsit
The document discusses job sequencing and scheduling techniques. It begins by defining job sequencing as the arrangement of tasks to be performed in a specified order. It then discusses several algorithms and methods for solving job sequencing problems, including tabu search, fuzzy TOPSIS, genetic algorithms, Johnson's rule, and mathematical modeling approaches. It also covers classification of jobs, performance metrics, and discusses modified time deviation as a heuristic technique to arrange job sequences to minimize total elapsed time.
Job Shop Scheduling Using Mixed Integer ProgrammingIJMERJOURNAL
The document describes four mixed integer programming models for job shop scheduling with different objectives:
1) Minimize makespan without due dates
2) Minimize makespan with due date constraints
3) Minimize total earliness to accomplish just-in-time manufacturing
4) Minimize total lateness to reduce lateness penalties
The models are solved and their computational performance is compared based on parameters like makespan, machine utilization, and time efficiency. The results show that adding due date and earliness/lateness constraints increases makespan and machine idle time, lowering utilization.
A case study on Machine scheduling and sequencing using Meta heuristicsIJERA Editor
Modern manufacturing systems are constantly increasing in complexity and become more agile in nature such
system has become more crucial to check feasibility of machine scheduling and sequencing because effective
scheduling and sequencing can yield increase in productivity due to maximum utilization of available resources
but when number of machine increases traditional scheduling methods e.g. Johnson‟s ,rule is becomes in
effective Due to the limitations involved in exhaustive enumeration, for such problems meta-heuristics has
become greater choice for solving NP hard problems because of their multi solution and strong neighbourhood
search capability in a reasonable time.
A M ULTI -O BJECTIVE B ASED E VOLUTIONARY A LGORITHM AND S OCIAL N ETWOR...IJCI JOURNAL
In this paper, a multi-objective based NSGA-II algo
rithm is proposed for dynamic job-shop scheduling
problem (DJSP) with random job arrivals and machine
breakdowns. In DJSP schedules are usually
inevitable due to various unexpected disruptions. T
o handle this problem, it is necessary to select
appropriate key machines at the beginning of the si
mulation instead of random selection. Thus, this pa
per
seeks to address on approach called social network
analysis method to identify the key machines of the
addressed DJSP. With identified key machines, the e
ffectiveness and stability of scheduling i.e., make
span
and starting time deviations of the computational c
omplex NP-hard problem has been solved with propose
d
multi-objective based hybrid NSGA-ll algorithm. Sev
eral experiments studies have been conducted and
comparisons have been made to demonstrate the effic
iency of the proposed approach with classical multi
-
objective based NSGA-II algorithm. The experimental
results illustrate that the proposed method is ver
y
effective in various shop floor conditions
Parallel Line and Machine Job Scheduling Using Genetic AlgorithmIRJET Journal
This document summarizes research on using a genetic algorithm to solve a parallel line and machine job scheduling problem. The objective is to minimize the makespan (completion time) of all jobs. A genetic algorithm is applied that represents possible job schedules as chromosomes. The fitness function evaluates schedules based on makespan. Genetic operators like crossover and mutation create new schedules from existing ones. The algorithm was tested on sample job data using a MATLAB program. Results showed the genetic algorithm approach can find optimal job allocations and schedules that minimize makespan for parallel line scheduling problems.
A Simulation Based Approach for Studying the Effect of Buffers on the Perform...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
IRJET- Integration of Job Release Policies and Job Scheduling Policies in...IRJET Journal
This document presents research on integrating job release policies and job scheduling policies in assembly job shop scheduling to minimize mean flow time and mean tardiness. A simulation model of an assembly job shop with different product structures was developed. An order release policy using backward scheduling was adopted to reduce unnecessary waiting times. Six dispatching rules were incorporated into the simulation model. The simulation was run both with and without integrating the order release policy. Analysis showed that integrating the order release policy and dispatching rules led to reductions in mean flow time and mean tardiness across all product structures.
Bi criteria scheduling on parallel machines under fuzzy processing timeboujazra
This paper addresses bi-criteria scheduling on parallel machines to optimize total tardiness and weighted flow time under fuzzy processing times. Total tardiness is minimized as the primary objective, and weighted flow time is minimized as the secondary objective without violating the primary objective. Fuzzy set theory is used to represent uncertainty in job processing times using triangular membership functions. An algorithm is proposed and tested through a numerical example to find optimal job sequences.
Modified heuristic time deviation Technique for job sequencing and Computatio...ijcsit
The document discusses job sequencing and scheduling techniques. It begins by defining job sequencing as the arrangement of tasks to be performed in a specified order. It then discusses several algorithms and methods for solving job sequencing problems, including tabu search, fuzzy TOPSIS, genetic algorithms, Johnson's rule, and mathematical modeling approaches. It also covers classification of jobs, performance metrics, and discusses modified time deviation as a heuristic technique to arrange job sequences to minimize total elapsed time.
Job Shop Scheduling Using Mixed Integer ProgrammingIJMERJOURNAL
The document describes four mixed integer programming models for job shop scheduling with different objectives:
1) Minimize makespan without due dates
2) Minimize makespan with due date constraints
3) Minimize total earliness to accomplish just-in-time manufacturing
4) Minimize total lateness to reduce lateness penalties
The models are solved and their computational performance is compared based on parameters like makespan, machine utilization, and time efficiency. The results show that adding due date and earliness/lateness constraints increases makespan and machine idle time, lowering utilization.
A case study on Machine scheduling and sequencing using Meta heuristicsIJERA Editor
Modern manufacturing systems are constantly increasing in complexity and become more agile in nature such
system has become more crucial to check feasibility of machine scheduling and sequencing because effective
scheduling and sequencing can yield increase in productivity due to maximum utilization of available resources
but when number of machine increases traditional scheduling methods e.g. Johnson‟s ,rule is becomes in
effective Due to the limitations involved in exhaustive enumeration, for such problems meta-heuristics has
become greater choice for solving NP hard problems because of their multi solution and strong neighbourhood
search capability in a reasonable time.
A M ULTI -O BJECTIVE B ASED E VOLUTIONARY A LGORITHM AND S OCIAL N ETWOR...IJCI JOURNAL
In this paper, a multi-objective based NSGA-II algo
rithm is proposed for dynamic job-shop scheduling
problem (DJSP) with random job arrivals and machine
breakdowns. In DJSP schedules are usually
inevitable due to various unexpected disruptions. T
o handle this problem, it is necessary to select
appropriate key machines at the beginning of the si
mulation instead of random selection. Thus, this pa
per
seeks to address on approach called social network
analysis method to identify the key machines of the
addressed DJSP. With identified key machines, the e
ffectiveness and stability of scheduling i.e., make
span
and starting time deviations of the computational c
omplex NP-hard problem has been solved with propose
d
multi-objective based hybrid NSGA-ll algorithm. Sev
eral experiments studies have been conducted and
comparisons have been made to demonstrate the effic
iency of the proposed approach with classical multi
-
objective based NSGA-II algorithm. The experimental
results illustrate that the proposed method is ver
y
effective in various shop floor conditions
Parallel Line and Machine Job Scheduling Using Genetic AlgorithmIRJET Journal
This document summarizes research on using a genetic algorithm to solve a parallel line and machine job scheduling problem. The objective is to minimize the makespan (completion time) of all jobs. A genetic algorithm is applied that represents possible job schedules as chromosomes. The fitness function evaluates schedules based on makespan. Genetic operators like crossover and mutation create new schedules from existing ones. The algorithm was tested on sample job data using a MATLAB program. Results showed the genetic algorithm approach can find optimal job allocations and schedules that minimize makespan for parallel line scheduling problems.
A Simulation Based Approach for Studying the Effect of Buffers on the Perform...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
IRJET- Integration of Job Release Policies and Job Scheduling Policies in...IRJET Journal
This document presents research on integrating job release policies and job scheduling policies in assembly job shop scheduling to minimize mean flow time and mean tardiness. A simulation model of an assembly job shop with different product structures was developed. An order release policy using backward scheduling was adopted to reduce unnecessary waiting times. Six dispatching rules were incorporated into the simulation model. The simulation was run both with and without integrating the order release policy. Analysis showed that integrating the order release policy and dispatching rules led to reductions in mean flow time and mean tardiness across all product structures.
Bi criteria scheduling on parallel machines under fuzzy processing timeboujazra
This paper addresses bi-criteria scheduling on parallel machines to optimize total tardiness and weighted flow time under fuzzy processing times. Total tardiness is minimized as the primary objective, and weighted flow time is minimized as the secondary objective without violating the primary objective. Fuzzy set theory is used to represent uncertainty in job processing times using triangular membership functions. An algorithm is proposed and tested through a numerical example to find optimal job sequences.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
AN EFFICIENT HEURISTIC ALGORITHM FOR FLEXIBLE JOB SHOP SCHEDULING WITH MAINTE...mathsjournal
This document summarizes a heuristic algorithm for solving the flexible job shop scheduling problem with preventive maintenance constraints. The objectives are to minimize makespan, total workload, and maximum machine workload.
The algorithm uses a constructive procedure to sequentially assign each operation (job or maintenance) to machines based on a calculated total cost (TC) value. TC considers factors like processing time, workload balance, and maintenance window compliance. Multiple parameter settings are tested to generate initial solutions. Computational results on benchmark problems show the heuristic finds good quality solutions very quickly, making it suitable for practical applications.
SIMULATION AND COMPARISON ANALYSIS OF DUE DATE ASSIGNMENT METHODS USING SCHED...IJCSES Journal
This paper presents a simulation and comparison analysis conducted to investigate the due-date
assignment methods through various scheduling rules. The due date assignment methods investigated are
flow time due date (FTDD) and total work content (TWK) method. Three scheduling rules are integrated in
the simulation for scheduling of jobs on machines. The performance of the study is evaluated based on the
configuration system of Hibret manufacturing and machine building Industry, subsidiary company of
Metals and Engineering Corporation were thoroughly considered. The performance of the system is
evaluated based on maximum tardiness, number of tardy jobs and total weighted tardiness. Simulation
experiments are carried in different scenarios through combining due-date assignment methods and
scheduling rules. A two factor Analysis of variance of the experiment result is performed to identify the
effect of due-date assignment methods and scheduling rules on the performance of the job shop system. The
least significant difference (LSD) method was used for performing comparisons in order to determine
which means differ from the other. The finding of the study reveals that FTDD methods gives less mean
value compared to TWK when evaluated by the three scheduling rules.
EFFICIENT SCHEDULING STRATEGY USING COMMUNICATION AWARE SCHEDULING FOR PARALL...ijdpsjournal
In the area of Computer Science, Parallel job scheduling is an important field of research. Finding a best
suitable processor on the high performance or cluster computing for user submitted jobs plays an
important role in measuring system performance. A new scheduling technique called communication aware
scheduling is devised and is capable of handling serial jobs, parallel jobs, mixed jobs and dynamic jobs.
This work focuses the comparison of communication aware scheduling with the available parallel job
scheduling techniques and the experimental results show that communication aware scheduling performs
better when compared to the available parallel job scheduling techniques.
Kubota, n. 1994: genetic algorithm with age structure and its application to ...ArchiLab 7
This paper proposes a new genetic algorithm called the age structured genetic algorithm (ASGA) to address issues of premature convergence and bias in traditional genetic algorithms. The ASGA introduces an age structure that allows parents and offspring to coexist in populations over multiple generations. The paper applies the ASGA to optimize the organization of a press machining line as an example of a self-organizing manufacturing system. Numerical simulations demonstrate that the ASGA improves the press line's makespan, or total processing time, by up to 10% compared to traditional genetic algorithms and performs best on more complex problem instances. The ASGA helps maintain genetic diversity in populations and finds better optimizations for scheduling flexible manufacturing systems.
Modeling of assembly line balancing for optimized number of stations and timeIAEME Publication
This document summarizes research on modeling assembly line balancing to optimize the number of stations and cycle time. It begins by classifying assembly line balancing problems based on objectives and problem structure. It then presents the Buxey 29 task precedence diagram and solves the problem to find feasible solutions with minimum cycle time for different numbers of stations (8, 9, 10 stations). The results show the total time remains 324 seconds for the optimal solution as more stations are added, while the cycle time decreases from 41 to 34 seconds. Increasing stations improves flexibility but also costs, so solutions must consider objectives and constraints.
The document summarizes research in the field of stochastic scheduling. It discusses three broad categories of stochastic scheduling models: 1) models for scheduling a batch of stochastic jobs, 2) multi-armed bandit models, and 3) models for scheduling queueing systems. For many models in these categories, relatively simple priority-index rules have been shown to optimize important performance objectives like expected flowtime. However, more complex models generally lack tractable optimal solutions. Recent research thus focuses on designing near-optimal heuristic policies.
IJREI_Selection model for material handling equipment’s used in flexible manu...Husain Mehdi
Material handling (MH) is important issue for every production site and has a great dependence upon the layout of the system. The important issue in the design of MH system is the selection of material handling equipment for every MH operation. Based upon the literature survey in this area, our purpose is to focus on the evaluation of the MHS-Layout of the system, due to their strong interdependence. The aim of this paper is to present a method for selection of material handling equipment (MHE) for flexible manufacturing system. In the first phase, the system consider major issues, rate of transfer, average time to transfer, flexibility etc., which is essential for the system. In second phase, the system selects the most feasible MHE types for every MH operation in a given application depends upon these major issues using fuzzy logic controller.
This document presents a genetic algorithm approach for scheduling jobs with burst times and priorities to find a schedule that is near or equal to the optimal shortest job first (SJF) schedule. It discusses related work on using genetic algorithms for scheduling problems. The proposed algorithm uses a genetic algorithm to generate priorities that are assigned to jobs to find a schedule with a total turnaround time close to the SJF schedule. Experimental results show that the genetic algorithm approach produces solutions very close to SJF and better than a priority-based algorithm in terms of total turnaround time.
6 intelligent design of a dynamic machine layoutQuốc Lê
The document proposes a new mathematical model for designing an optimal machine layout for each period of a stochastic dynamic facility layout problem (SDFLP) in flexible manufacturing systems (FMS). The model considers product demands as random variables with known probability density functions that change randomly between periods. It formulates the SDFLP using a quadratic assignment problem (QAP) model that minimizes the total material handling and rearrangement costs over multiple periods. Due to the complexity of the problem, a simulated annealing (SA) metaheuristic is used to solve the mathematical model within a reasonable computational time.
Novel Heuristics for no-Wait Two Stage Multiprocessor Flow Shop with Probable...IRJET Journal
This document presents a study on scheduling algorithms for a two-stage manufacturing flow shop problem with rework and sequence-dependent setup times. It introduces novel heuristic algorithms like discrete particle swarm optimization, adapted imperialist competitive algorithm, and adapted invasive weed optimization. These algorithms are evaluated based on their ability to minimize the makespan (total completion time) for a given set of jobs in the flow shop. The adapted invasive weed optimization approach achieved superior performance compared to the other algorithms in computational experiments on this scheduling problem.
A GUI-driven prototype for synthesizing self-adaptation decisionjournalBEEI
This document describes a GUI-driven prototype for assessing the synthesis of self-adaptation decisions. The prototype allows users to configure simulation parameters, execute synthesis simulations, and visualize the results. It integrates libraries for model checking, charting, and graph visualization. The prototype is demonstrated on a use case involving application deployment decisions in an autonomic cloud computing environment. The prototype aims to ease experimentation and evaluation of synthesis-driven approaches for self-adaptive systems.
A Model for Optimum Scheduling Of Non-Resumable Jobs on Parallel Production M...IOSR Journals
This document presents a mathematical model for optimizing the scheduling of non-resumable jobs on parallel production machines that are subject to multiple fixed periods of unavailability. The problem is formulated as an integer linear programming model to minimize the makespan. Two algorithms are proposed to solve the problem - the first uses the longest processing time rule to generate an initial solution and upper bound, and the second is a greedy algorithm that iteratively achieves an optimal solution by backtracking. The algorithms are implemented in software and validated using numerical examples and industrial case studies, showing makespan reductions of 49% and 40% compared to actual industry scheduling.
Nitt paper A fuzzy multi-objective based un-related parallel Machine Schedu...Arudhra N
This paper addresses a multi-objective scheduling problem to minimize makespan, tardiness, load variation, flow time, and secondary resource constraints for an unrelated parallel machine scheduling problem. A multi-objective evolutionary algorithm called Fuzzy-Non-dominated Sorting Genetic Algorithm (FNSGA-II) is proposed to solve this computationally challenging problem. The performance of FNSGA-II is validated on randomly generated test problems and is found to perform reasonably well in terms of quality, computational time, diversity and spacing metrics. The paper formulates the scheduling problem as a fuzzy mixed-integer non-linear programming model and describes the implementation of FNSGA-II using evolutionary operators like crossover, mutation, and non-dom
6months industrial training in fuzzy logic, jalandhardeepikakaler1
e2matrix is a leading Web Design and Development Company now in the field of Industrial training. We provide you 6 Month/6 Week Industrial training in PhP,Web Designing, Java, Dot Net, android Applications.
we also provide work for various technoligies with additional facilities-
RESEARCH PAPERS
OBJECTIVES
SYNOPSIS
IMPLEMENTATION
DOCUMENTATION
REPORT WRITING
PAPER PUBLICATION
Address-Opp. Phagwara Bus Stand, Above Bella
Pizza, Handa City Center, Phagwara,punjab
email addres-e2matrixphagwara@gmail.com
jalandhare2matrix@gmail.com
WEBSITE-www.e2matrix.com
CONTACT NUMBER --
09041262727
07508509730
7508509709
The document discusses the history and applications of fuzzy logic control. It describes how fuzzy logic was first introduced in 1965 and began being applied in various industries starting in the 1970s. By the 1990s, fuzzy logic had become a standard control technique, especially for multi-variable control systems. The document outlines the basic elements of a fuzzy logic system and provides an example of how fuzzy logic can be used to control a container crane.
The document describes a virtual ordering system created by students to address the problem of customers being unsatisfied with long lines or walking to stalls to order food. A paper prototype was created and evaluated, with findings that users could understand the flow but needed guidelines. A computer prototype was then made and evaluated, with findings that users could easily follow the flow and order food quickly in the real system. The virtual ordering system was designed using a virtual reality interface to allow customers to order food from cafes in a user-friendly way.
This document presents a summary of fuzzy logic and its applications to computer aided manufacturing. It introduces fuzzy logic as a way to process imprecise data and mimic human control logic. The basic concepts are explained, including fuzzy sets that have partial truth values between 0 and 1. An example is provided of how fuzzy logic can be used for temperature regulation. The steps in fuzzy logic control are outlined as fuzzification, rule specification, and defuzzification. Applications discussed include anti-lock braking systems, flight control, and using fuzzy logic controllers to adjust feed rates and position presses in manufacturing.
Fuzzy logic is a form of logic that accounts for partial truth and intermediate values between true and false. It is used in control systems to mimic how humans apply fuzzy concepts like "cold" or "hot" temperature. Some key applications of fuzzy logic include temperature controllers, washing machines, air conditioners, and anti-lock braking systems. Fuzzy logic controllers use if-then rules to determine outputs based on fuzzy inputs and degrees of membership rather than binary logic.
Pid controller tuning using fuzzy logicRoni Roshni
This document provides an overview of tuning a PID controller with fuzzy logic. It introduces fuzzy logic and discusses how it can be applied to PID tuning. Specifically, it discusses using fuzzy set-point weighting to tune the PID controller by determining the proportional weighting factor b(t) using a fuzzy inference system based on the error e(t) and change in error. It also discusses traditional Ziegler-Nichols tuning and compares the performance of fixed versus fuzzy set-point weighting tuning. The conclusion is that fuzzy logic provides benefits like balancing rise time and overshoot to obtain better performance than traditional methods.
This document discusses hybrid intelligent systems that combine different technologies such as neural networks, fuzzy systems, and expert systems. It provides examples of neural expert systems, which combine neural networks and rule-based expert systems, and neuro-fuzzy systems, which integrate neural networks with fuzzy logic systems. The key benefits of these hybrid systems include gaining the learning and parallel processing abilities of neural networks as well as the transparency and human-like knowledge representation of fuzzy and expert systems.
This document provides an overview of fuzzy logic and fuzzy set theory with examples from image processing. Some key points:
- Fuzzy set theory was coined by Lofti Zadeh in 1965 and allows for degrees of membership rather than binary true/false values. Almost all real-world classes are fuzzy.
- Fuzzy logic handles imprecise concepts like "tall person" through membership functions and handles inferences through generalized modus ponens.
- Fuzzy logic has been applied to fields like image processing, where concepts like "light blue" are fuzzy, and speech recognition by assigning fuzzy values to phonemes.
- Techniques discussed include fuzzy membership functions, aggregation operations, alpha cuts, linguistic
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
AN EFFICIENT HEURISTIC ALGORITHM FOR FLEXIBLE JOB SHOP SCHEDULING WITH MAINTE...mathsjournal
This document summarizes a heuristic algorithm for solving the flexible job shop scheduling problem with preventive maintenance constraints. The objectives are to minimize makespan, total workload, and maximum machine workload.
The algorithm uses a constructive procedure to sequentially assign each operation (job or maintenance) to machines based on a calculated total cost (TC) value. TC considers factors like processing time, workload balance, and maintenance window compliance. Multiple parameter settings are tested to generate initial solutions. Computational results on benchmark problems show the heuristic finds good quality solutions very quickly, making it suitable for practical applications.
SIMULATION AND COMPARISON ANALYSIS OF DUE DATE ASSIGNMENT METHODS USING SCHED...IJCSES Journal
This paper presents a simulation and comparison analysis conducted to investigate the due-date
assignment methods through various scheduling rules. The due date assignment methods investigated are
flow time due date (FTDD) and total work content (TWK) method. Three scheduling rules are integrated in
the simulation for scheduling of jobs on machines. The performance of the study is evaluated based on the
configuration system of Hibret manufacturing and machine building Industry, subsidiary company of
Metals and Engineering Corporation were thoroughly considered. The performance of the system is
evaluated based on maximum tardiness, number of tardy jobs and total weighted tardiness. Simulation
experiments are carried in different scenarios through combining due-date assignment methods and
scheduling rules. A two factor Analysis of variance of the experiment result is performed to identify the
effect of due-date assignment methods and scheduling rules on the performance of the job shop system. The
least significant difference (LSD) method was used for performing comparisons in order to determine
which means differ from the other. The finding of the study reveals that FTDD methods gives less mean
value compared to TWK when evaluated by the three scheduling rules.
EFFICIENT SCHEDULING STRATEGY USING COMMUNICATION AWARE SCHEDULING FOR PARALL...ijdpsjournal
In the area of Computer Science, Parallel job scheduling is an important field of research. Finding a best
suitable processor on the high performance or cluster computing for user submitted jobs plays an
important role in measuring system performance. A new scheduling technique called communication aware
scheduling is devised and is capable of handling serial jobs, parallel jobs, mixed jobs and dynamic jobs.
This work focuses the comparison of communication aware scheduling with the available parallel job
scheduling techniques and the experimental results show that communication aware scheduling performs
better when compared to the available parallel job scheduling techniques.
Kubota, n. 1994: genetic algorithm with age structure and its application to ...ArchiLab 7
This paper proposes a new genetic algorithm called the age structured genetic algorithm (ASGA) to address issues of premature convergence and bias in traditional genetic algorithms. The ASGA introduces an age structure that allows parents and offspring to coexist in populations over multiple generations. The paper applies the ASGA to optimize the organization of a press machining line as an example of a self-organizing manufacturing system. Numerical simulations demonstrate that the ASGA improves the press line's makespan, or total processing time, by up to 10% compared to traditional genetic algorithms and performs best on more complex problem instances. The ASGA helps maintain genetic diversity in populations and finds better optimizations for scheduling flexible manufacturing systems.
Modeling of assembly line balancing for optimized number of stations and timeIAEME Publication
This document summarizes research on modeling assembly line balancing to optimize the number of stations and cycle time. It begins by classifying assembly line balancing problems based on objectives and problem structure. It then presents the Buxey 29 task precedence diagram and solves the problem to find feasible solutions with minimum cycle time for different numbers of stations (8, 9, 10 stations). The results show the total time remains 324 seconds for the optimal solution as more stations are added, while the cycle time decreases from 41 to 34 seconds. Increasing stations improves flexibility but also costs, so solutions must consider objectives and constraints.
The document summarizes research in the field of stochastic scheduling. It discusses three broad categories of stochastic scheduling models: 1) models for scheduling a batch of stochastic jobs, 2) multi-armed bandit models, and 3) models for scheduling queueing systems. For many models in these categories, relatively simple priority-index rules have been shown to optimize important performance objectives like expected flowtime. However, more complex models generally lack tractable optimal solutions. Recent research thus focuses on designing near-optimal heuristic policies.
IJREI_Selection model for material handling equipment’s used in flexible manu...Husain Mehdi
Material handling (MH) is important issue for every production site and has a great dependence upon the layout of the system. The important issue in the design of MH system is the selection of material handling equipment for every MH operation. Based upon the literature survey in this area, our purpose is to focus on the evaluation of the MHS-Layout of the system, due to their strong interdependence. The aim of this paper is to present a method for selection of material handling equipment (MHE) for flexible manufacturing system. In the first phase, the system consider major issues, rate of transfer, average time to transfer, flexibility etc., which is essential for the system. In second phase, the system selects the most feasible MHE types for every MH operation in a given application depends upon these major issues using fuzzy logic controller.
This document presents a genetic algorithm approach for scheduling jobs with burst times and priorities to find a schedule that is near or equal to the optimal shortest job first (SJF) schedule. It discusses related work on using genetic algorithms for scheduling problems. The proposed algorithm uses a genetic algorithm to generate priorities that are assigned to jobs to find a schedule with a total turnaround time close to the SJF schedule. Experimental results show that the genetic algorithm approach produces solutions very close to SJF and better than a priority-based algorithm in terms of total turnaround time.
6 intelligent design of a dynamic machine layoutQuốc Lê
The document proposes a new mathematical model for designing an optimal machine layout for each period of a stochastic dynamic facility layout problem (SDFLP) in flexible manufacturing systems (FMS). The model considers product demands as random variables with known probability density functions that change randomly between periods. It formulates the SDFLP using a quadratic assignment problem (QAP) model that minimizes the total material handling and rearrangement costs over multiple periods. Due to the complexity of the problem, a simulated annealing (SA) metaheuristic is used to solve the mathematical model within a reasonable computational time.
Novel Heuristics for no-Wait Two Stage Multiprocessor Flow Shop with Probable...IRJET Journal
This document presents a study on scheduling algorithms for a two-stage manufacturing flow shop problem with rework and sequence-dependent setup times. It introduces novel heuristic algorithms like discrete particle swarm optimization, adapted imperialist competitive algorithm, and adapted invasive weed optimization. These algorithms are evaluated based on their ability to minimize the makespan (total completion time) for a given set of jobs in the flow shop. The adapted invasive weed optimization approach achieved superior performance compared to the other algorithms in computational experiments on this scheduling problem.
A GUI-driven prototype for synthesizing self-adaptation decisionjournalBEEI
This document describes a GUI-driven prototype for assessing the synthesis of self-adaptation decisions. The prototype allows users to configure simulation parameters, execute synthesis simulations, and visualize the results. It integrates libraries for model checking, charting, and graph visualization. The prototype is demonstrated on a use case involving application deployment decisions in an autonomic cloud computing environment. The prototype aims to ease experimentation and evaluation of synthesis-driven approaches for self-adaptive systems.
A Model for Optimum Scheduling Of Non-Resumable Jobs on Parallel Production M...IOSR Journals
This document presents a mathematical model for optimizing the scheduling of non-resumable jobs on parallel production machines that are subject to multiple fixed periods of unavailability. The problem is formulated as an integer linear programming model to minimize the makespan. Two algorithms are proposed to solve the problem - the first uses the longest processing time rule to generate an initial solution and upper bound, and the second is a greedy algorithm that iteratively achieves an optimal solution by backtracking. The algorithms are implemented in software and validated using numerical examples and industrial case studies, showing makespan reductions of 49% and 40% compared to actual industry scheduling.
Nitt paper A fuzzy multi-objective based un-related parallel Machine Schedu...Arudhra N
This paper addresses a multi-objective scheduling problem to minimize makespan, tardiness, load variation, flow time, and secondary resource constraints for an unrelated parallel machine scheduling problem. A multi-objective evolutionary algorithm called Fuzzy-Non-dominated Sorting Genetic Algorithm (FNSGA-II) is proposed to solve this computationally challenging problem. The performance of FNSGA-II is validated on randomly generated test problems and is found to perform reasonably well in terms of quality, computational time, diversity and spacing metrics. The paper formulates the scheduling problem as a fuzzy mixed-integer non-linear programming model and describes the implementation of FNSGA-II using evolutionary operators like crossover, mutation, and non-dom
6months industrial training in fuzzy logic, jalandhardeepikakaler1
e2matrix is a leading Web Design and Development Company now in the field of Industrial training. We provide you 6 Month/6 Week Industrial training in PhP,Web Designing, Java, Dot Net, android Applications.
we also provide work for various technoligies with additional facilities-
RESEARCH PAPERS
OBJECTIVES
SYNOPSIS
IMPLEMENTATION
DOCUMENTATION
REPORT WRITING
PAPER PUBLICATION
Address-Opp. Phagwara Bus Stand, Above Bella
Pizza, Handa City Center, Phagwara,punjab
email addres-e2matrixphagwara@gmail.com
jalandhare2matrix@gmail.com
WEBSITE-www.e2matrix.com
CONTACT NUMBER --
09041262727
07508509730
7508509709
The document discusses the history and applications of fuzzy logic control. It describes how fuzzy logic was first introduced in 1965 and began being applied in various industries starting in the 1970s. By the 1990s, fuzzy logic had become a standard control technique, especially for multi-variable control systems. The document outlines the basic elements of a fuzzy logic system and provides an example of how fuzzy logic can be used to control a container crane.
The document describes a virtual ordering system created by students to address the problem of customers being unsatisfied with long lines or walking to stalls to order food. A paper prototype was created and evaluated, with findings that users could understand the flow but needed guidelines. A computer prototype was then made and evaluated, with findings that users could easily follow the flow and order food quickly in the real system. The virtual ordering system was designed using a virtual reality interface to allow customers to order food from cafes in a user-friendly way.
This document presents a summary of fuzzy logic and its applications to computer aided manufacturing. It introduces fuzzy logic as a way to process imprecise data and mimic human control logic. The basic concepts are explained, including fuzzy sets that have partial truth values between 0 and 1. An example is provided of how fuzzy logic can be used for temperature regulation. The steps in fuzzy logic control are outlined as fuzzification, rule specification, and defuzzification. Applications discussed include anti-lock braking systems, flight control, and using fuzzy logic controllers to adjust feed rates and position presses in manufacturing.
Fuzzy logic is a form of logic that accounts for partial truth and intermediate values between true and false. It is used in control systems to mimic how humans apply fuzzy concepts like "cold" or "hot" temperature. Some key applications of fuzzy logic include temperature controllers, washing machines, air conditioners, and anti-lock braking systems. Fuzzy logic controllers use if-then rules to determine outputs based on fuzzy inputs and degrees of membership rather than binary logic.
Pid controller tuning using fuzzy logicRoni Roshni
This document provides an overview of tuning a PID controller with fuzzy logic. It introduces fuzzy logic and discusses how it can be applied to PID tuning. Specifically, it discusses using fuzzy set-point weighting to tune the PID controller by determining the proportional weighting factor b(t) using a fuzzy inference system based on the error e(t) and change in error. It also discusses traditional Ziegler-Nichols tuning and compares the performance of fixed versus fuzzy set-point weighting tuning. The conclusion is that fuzzy logic provides benefits like balancing rise time and overshoot to obtain better performance than traditional methods.
This document discusses hybrid intelligent systems that combine different technologies such as neural networks, fuzzy systems, and expert systems. It provides examples of neural expert systems, which combine neural networks and rule-based expert systems, and neuro-fuzzy systems, which integrate neural networks with fuzzy logic systems. The key benefits of these hybrid systems include gaining the learning and parallel processing abilities of neural networks as well as the transparency and human-like knowledge representation of fuzzy and expert systems.
This document provides an overview of fuzzy logic and fuzzy set theory with examples from image processing. Some key points:
- Fuzzy set theory was coined by Lofti Zadeh in 1965 and allows for degrees of membership rather than binary true/false values. Almost all real-world classes are fuzzy.
- Fuzzy logic handles imprecise concepts like "tall person" through membership functions and handles inferences through generalized modus ponens.
- Fuzzy logic has been applied to fields like image processing, where concepts like "light blue" are fuzzy, and speech recognition by assigning fuzzy values to phonemes.
- Techniques discussed include fuzzy membership functions, aggregation operations, alpha cuts, linguistic
This document provides an overview of fuzzy logic and its applications. It begins with motivations for fuzzy logic by discussing limitations of crisp sets and fuzzy sets as an alternative approach. It then defines fuzzy sets and fuzzy logic operations. It describes how fuzzy logic systems work by combining fuzzy sets and logic operations. Several example applications are mentioned, including industrial control systems and modeling human decision making. The document concludes by noting fuzzy logic has been applied in many domains and there are ongoing developments in fuzzy logic approaches.
The document discusses the semantic web and ontology inference. It describes how ontologies are used on the semantic web to represent knowledge through concepts and relationships. It then explains different types of ontology inference including TBox inference, ABox inference, and rule-based inference using languages like SWRL. Examples of inference engines that support ontology reasoning are also provided.
Reusability is an only one best direction to increase developing productivity and maintainability of application. One must first search for good tested software component and reusable. Developed Application software by one programmer can be shown useful for others also component. This is proving that code specifics to application requirements can be also reused in develop projects related with same requirements. The main aim of this paper proposed a way for reusable module. An process that takes source code as a input that will helped to take the decision approximately which particular software, reusable artefacts should be reused or not.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The document discusses an improved error detection and data recovery architecture for motion estimation testing applications. It presents a residue-and-quotient (RQ) code-based design to embed into motion estimation for detecting and recovering from errors in processing elements. Experimental results show the design can detect errors and recover data with acceptable overhead in area and timing. It also performs satisfactorily in terms of throughput and reliability for motion estimation testing.
SPSNYC - Authentication, Authorization, and Identity – More than meets the eye…Scott Hoag
In today’s complex market place of corporate partnerships and relationships, sharing information is pertinent to ensuring that business operations are conducted in a secure computing environment with trusted entities being provided access to protected information.
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As a part of this session we will demonstrate different authentication and authorization configurations that are common place in today’s business settings to include when to use:
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• ADFS as a Trusted Identity Provider
• Threat Management Gateway with Kerberos Constrained Delegation using client certs
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SPSRIC - SharePoint 2013 – A brief overview for IT ProsScott Hoag
Hot off the press, SharePoint 2013 attained Release to Manufacture in October 2012 and is speeding ahead to general availability in early 2013. Interesting in learning what’s new and different? Then come and learn more about new capabilities in the product such as Shredded Storage and Distributed Caching among others as well as how the migration story changes for SharePoint 2013.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Improving Power Efficiency in Cooperative Diversity and Mimo Systems by Using...IJERA Editor
In this paper, we propose a new simple relayingstrategy based on bit-interleaved convolutionally coded starquadrature amplitude modulation (QAM) along with coherent/ noncoherent detection. Exploiting this property, a hard limiter is used to enhance power amplifier (PA) efficiency at the relay.here we are using the higher order modulation for improving relay communication and also employ the accurate relay technique.Moreover, we show that the proposedapproach retains differential detectability, which results in a significant reduction of receiver complexity with robustness against phase ambiguityBy analyzing our proposed method in terms of asymptotic pairwise error probability(PEP),Furthermore, theeffectiveness of the proposed scheme in terms of PA efficiency is confirmed by comparing the statistical distributions of the corresponding instantaneous signal power.and also implement the PEP in MIMO systems for improving the power efficiency.All the theoretical results agree with those obtained by computer simulations.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Flexible ac transmission systems (FACTS), network congestion, Ordinal Optimiz...IJERA Editor
IS 800 in 2007, follows Limit State Design method for general construction for steel but provision for limit state design of light gauge cold form steel has not been made in it. IS 801-1975 provides the guild lines for use of cold formed light gauge steel structural members in general building construction which follows working stress design. This code is under revision. In this paper, in order to understand limit strength of light gauge cold form steel section in flexure a finite element analyses has been carried out on light gauge cold form built up I sections with different heights and thicknesses to asses limit load and modes of failure. Elastic and inelastic flexural strength and deformation behavior have been studied and finally a parametric study was undertaken to understand the influence of height, thickness on its structural behavior. It has been observed that light gauge cold form section with low H/t aspect ratio posses higher ratios of limiting load to elastic load.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This document discusses scheduling optimization for flexible manufacturing systems using genetic algorithms. It begins with an introduction to flexible manufacturing systems and some of the challenges in scheduling their operations. The author then reviews previous research on scheduling in flexible manufacturing systems using various methods like heuristics, mathematical programming, and metaheuristics. The paper goes on to present a genetic algorithm approach for scheduling a flexible manufacturing system with the goals of minimizing machine idle time and penalty costs for missed deadlines. Software is developed to obtain an optimal schedule. The genetic algorithm finds the global optimum schedule after 1700 generations.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Investigating and Classifying the Applications of Flexible Manufacturing Syst...IOSR Journals
The recent manufacturing environment is characterized as having diverse products due to mass
customization, short production lead-time, and unstable customer demand. Today, the need for flexibility, quick
responsiveness, and robustness to system uncertainties in production scheduling decisions has increased
significantly. In traditional job shops, tooling is usually assumed as a fixed resource. However, when tooling
resource is shared among different machines, a greater product variety, routing flexibility with a smaller tool
inventory can be realized. Such a strategy is usually enabled by an automatic tool changing mechanism and tool
delivery system to reduce the time for tooling setup, hence allows parts to be processed in small batches. In this
research, a dynamic scheduling problem under flexible tooling resource constraints is studied. An integrated
approach is proposed to allow two levels of hierarchical, dynamic decision making for job scheduling and tool
flow control in Automated Manufacturing Systems. It decomposes the overall problem into a series of static subproblems
for each scheduling window, handles random disruptions by updating job ready time, completion
time, and machine status on a rolling horizon basis, and considers the machine availability explicitly in
generating schedules. Two types of manufacturing system models are used in simulation studies to test the
effectiveness of the proposed dynamic scheduling approach. First, hypothetical models are generated using
some generic shop flow structures (e.g. flexible flow shops, job shops, and single-stage systems) and
configurations(Insup,Um.,et al.,2009).They are tested to provide the empirical evidence about how well the
proposed approach performs for the general automated manufacturing systems where parts have alternative
routings. Second, a model based on a real industrial flexible manufacturing system was used to test the
effectiveness of the proposed approach when machine types, part routing, tooling, and other production
parameters closely mimic to the real flexible manufacturing operations.
Job-shop manufacturing environment requires planning of schedules for the systems of low-volume having numerous variations. For a job-shop scheduling, ‘k’ number of operations and ‘n’ number of jobs on ‘m’ number of machines processed through an assured objective function to be minimized (makespan). This paper presents a capable genetic algorithm for the job-shop scheduling problems among operating parameters such as random population generation with a population size of 50, operation based chromosome structure, tournament selection as selection scheme, 2-point random crossover with probability 80%, 2-point mutation with probability 20%, elitism, repairing of chromosomes and no. of iteration is 1000. An algorithm is programmed for job shop scheduling problem using MATLAB 2009 a 7.8. The proposed genetic algorithm with certain operating parameters is applied to the two case studies taken from literature. The results also show that genetic algorithm is the best optimization technique for solving the scheduling problems of job shop manufacturing systems evolving shortest processing time and transportation time due to its implications to more practical and integrated problems.
Comparison of Dynamic Scheduling Techniques in Flexible Manufacturing SystemIJERA Editor
Scheduling is an important tool in the manufacturing area since productivity is inherently linked to how well the resources are used to increase efficiency and reduce waste. The present article analyzes and provides comparison of modern techniques used for solving dynamic scheduling problem in flexible manufacturing system. These techniques are often impractical in dynamic real world environments where there are complex constraints and a variety of unexpected disruptions. This paper defines the modern techniques of dynamic scheduling and provides a literature survey of scheduling which are presented in recent few years. The principles of several dynamic scheduling techniques, namely dispatching rules, heuristics, genetic algorithms and artificial intelligence techniques are describe in details and comparison of their potential.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Quasi-Static Evaluation of a Modular and Reconfigurable Manufacturing CellHillary Green
This document presents a novel modular and reconfigurable manufacturing cell (MRMC) system that aims to provide flexible manufacturing capabilities. Some key points:
- The MRMC system consists of modular manipulation hardware and software that can be quickly configured and reconfigured for different assembly and packaging applications.
- It uses a unique interconnect design to allow mechanical and electrical connection between modules. Distributed intelligence and self-locating software enables automatic configuration.
- Analytical evaluation of precision shows the MRMC maintains necessary accuracy and repeatability for tasks like pick-and-place despite reconfiguration.
- The goal is to offer a low-cost, low-risk solution for prototyping and low-volume manufacturing through
Improving layout and workload of manufacturing system using Delmia Quest simu...AM Publications
This paper describes a case study of analysis and optimization of the facility layout in a manufacturing cell
using a systematic search method and a Quest computer simulation model with graphical representation of the
manufacturing processes. The simulation model objective was to obtain Layout design to achieve a high productivity in the
flexible manufacturing system (FMS), to determine bottleneck locations and what the optimal batch size should be. The
Quest software proved to be a powerful tool in assessing what changes should be made to a manufacturing cell before
incurring manufacturing improvements and/or performing actual capital investments. The aim of this study is to get
an understanding of the cell and its behaviour regarding production and to use the simulation software to change,
analyse and improve the cell.
Artificial Neural Networks can achieve high degree of computation rates by
employing a massive number of simple processing elements with a high degree of
connectivity between elements. In this paper an attempt is made to present a Constraint
Satisfaction Adaptive Neural Network (CSANN) to solve the generalized job-shop
scheduling problem and it shows how to map a difficult constraint satisfaction job-shop
scheduling problem onto a simple neural net, where the number of neural processors equals
the number of operations, and the number of interconnections grows linearly with the total
number of operations. The proposed neural network can be easily constructed and can adjust
its weights of connections based on the sequence and resource constraints of the job-shop
scheduling problem during its processing. Simulation studies have shown that the proposed
neural network produces better solutions to job-shop scheduling problem.
This document provides a critical review of literature on scheduling and control of flexible manufacturing systems (FMS). It begins with an introduction to FMS and discusses how the operations problems of FMS can be broadly classified into planning, scheduling, and control. The review is then presented from multiple viewpoints: the methodology used (including mathematical programming, heuristics, simulation, and artificial intelligence approaches), applications perspective, time horizon considered, and FMS factors addressed. Future research directions are also suggested.
This document discusses flexible manufacturing systems (FMS). It begins by introducing FMS and explaining why manufacturing industries are adopting them. It then defines flexibility and describes seven types of flexibility that FMS can provide: machine, production, mix, product, routing, volume, and expansion flexibility. The document also compares attributes of flexible versus conventional manufacturing systems. Finally, it discusses the role of FMS in computer integrated manufacturing environments and provides an example decision tree to illustrate how FMS can help companies manage risk and uncertainty about future market conditions.
Planning and Scheduling of a Corrugated Cardboard Manufacturing Process in IoTijtsrd
The automation has revolutionized the traditional product development scheme by using advanced design and manufacturing technologies such as computer aided design, process planning, and scheduling. However, research in this field was still based mostly on experimentation, as most manufacturing companies did not use simulation techniques in the implementation of their manufacturing planning and scheduling process. In order to address this problem, software developers have put simulation software tools in the market such as Enterprise Resource Planning ERP , Advanced Planning and Scheduling APS , and Risk based Planning and Scheduling RPS systems. In this paper, a methodology to model high degree of accuracy for the production floor, the planning and scheduling of corrugated cardboard manufacturing process through RPS simulation in Internet of Things IoT environment is established. The RPS model is able to generate a deterministic schedule without randomness, create a risk analysis of the planning and scheduling, and handle the uncertainty. Bruno Kemen | Sarhan M. Musa "Planning and Scheduling of a Corrugated Cardboard Manufacturing Process in IoT" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, URL: https://www.ijtsrd.com/papers/ijtsrd37965.pdf Paper URL : https://www.ijtsrd.com/engineering/electrical-engineering/37965/planning-and-scheduling-of-a-corrugated-cardboard-manufacturing-process-in-iot/bruno-kemen
The document discusses the integration of process planning and scheduling in flexible manufacturing systems. It provides background on process planning, which specifies the operations, tools and machines needed to produce a product. Scheduling assigns manufacturing resources to operations over time. Traditionally these were separate functions, but integrating them can improve system performance and decision making. The document compares different approaches to integration, where process plans are generated based on current shop floor status and resources, and an optimal plan and schedule are selected to allocate operations to machines and time. Integrating the two functions helps address problems that arise when they are performed separately.
AN ADVANCED PRODUCTION PLANNING AND SCHEDULING SYSTEM FOR BATCH PROCESS INDUSTRYEmily Smith
This document presents an advanced production planning and scheduling (APPS) model for batch process industries. The model aims to minimize total costs including production, inventory holding, idle time, and lateness costs. It considers characteristics of batch processes like minimum order quantities, inventory levels, setup times, and processing times. The model divides the APPS problem into determining an optimal master production schedule and operations schedule. It was tested on empirical data from batch process industries and implemented in a real-world case study.
Improving the Performance of Mapping based on Availability- Alert Algorithm U...AM Publications
Performance of Mapping can be improved and it is needed arise in several fields of science and engineering.
They'll be parallelized in master-worker fashion and relevant programming ways have been projected to cut back
applications. In existing system, the performance of application is considered only for homogenous systems due to simplicity.
In this we use Availability-Alert algorithm using Poisson arrival to extend our approach for Heterogeneous systems in Multi
core Architecture systems. Our proposed algorithm also considers the requirement needed for the application for their
execution in Heterogeneous systems in Multi core Architecture systems while maintaining good performance. Performance
prediction errors are minimized by using this approach at the end of the execution. We present simulation results to quantify
the benefits of our approach.
Optimization of Assembly Line and Plant Layout in a Mass Production Industry...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Modeling and Analysis of Flexible Manufacturing System with FlexSimijceronline
Flexible manufacturing system (FMS) is a highly integrated manufacturing system. The relation between its components is very complex. The mathematical programming approaches are very difficult to solve for very complex system so the simulation of FMS is widely used to analyze its performance measures. Also the FMS components are very sophisticated and costly. If FMS has to be implemented then it is better to analyze its results using simulation which involves no loss of money, resource and labour time. As a typical discrete event system FMS have been studied in such aspects as modeling and performance analysis. In this paper, a concept and implementation of the Flexsim for measuring and analysis of performance measures of FMS is applied. The other well defined mathematical technique, i.e. bottleneck technique has also been applied for the purpose of comparison and verification of the simulation results. An example FMS has been taken into consideration and its flexsim model and mathematical model has been constructed. Several performance measures have been used to evaluate system performance. And it has been found that the simulation techniques are easy to analyze the complex fexible manufacturing system.
This document discusses adaptive system-level scheduling under fluid traffic flow conditions in multiprocessor systems. It proposes a scheduling mechanism that accounts for traffic-centric system design. The mechanism evaluates scheduling methods based on effectiveness, robustness, and flexibility. It also introduces a processor-FPGA scheduling approach that reduces schedule length by taking advantage of FPGA reconfiguration. Simulation results show that processor-FPGA scheduling outperforms multiprocessor-only scheduling under certain traffic conditions. Future work will focus on formulating a traffic-centric scheduling method.
In a multiprogramming system, multiple processes exist concurrently in main memory. Each process alternates between using a processor and waiting for some event to occur, such as the completion of an I O operation. The processor or processors are kept busy by executing one process while the others wait. The key to multiprogramming is scheduling. CPU scheduling deals with the problem of deciding which of the processes in the ready queue is to be allocated the CPU. By switching the CPU among processor the operating system can make the computer more productive. Scheduling affectes the performance of the system because it determines which processes will wait and which will progress. In this paper, simulation of various scheduling algorithm First Come First Served FCFS , Round Robin RR , Shortest Process Next SPN and Shortest Remaining Time SRT is done over C Daw Khin Po ""Simulation of Process Scheduling Algorithms"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25124.pdf
Paper URL: https://www.ijtsrd.com/computer-science/operating-system/25124/simulation-of-process-scheduling-algorithms/daw-khin-po
This paper examines using a shifting bottleneck heuristic algorithm to minimize the makespan of a job shop production system at Dejena Aviation Industry in Ethiopia. The authors collected secondary data on five machines processing five jobs. Applying the shifting bottleneck algorithm resulted in an 8.33% reduction in total makespan. Machine one (41%) and three (36%) were the least utilized, while machine three (64%) and five (59%) were the busiest. The paper reviews literature on job shop scheduling and shifting bottleneck approaches, provides background on modeling job shops, and describes the shifting bottleneck algorithm used in the study.
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1. Miss. Ashwini. A. Mate Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 6), July 2014, pp.104-111
www.ijera.com 104 | P a g e
Scheduling By Using Fuzzy Logic in Manufacturing Miss. Ashwini. A. Mate1, Dr. I. P. Keswani2 Department of industrial engineering RKNEC, NAGPUR Department of industrial engineering RKNEC, NAGPUR Abstract This paper represents the scheduling process in furniture manufacturing unit. It gives the fuzzy logic application in flexible manufacturing system. Flexible manufacturing systems are production system in furniture manufacturing unit. FMS consist of same multipurpose numerically controlled machines. Here in this project the scheduling has been done in FMS by using fuzzy logic tool in Matlab software. The fuzzy logic based scheduling model in this paper will deals with the job and best alternative route selection with multi-criteria of machine. Here two criteria for job and sequencing and routing with rules. This model is applicable to the scheduling of any manufacturing industry. Keywords: Scheduling, FMS, Fuzzy logic, matlab, sequencing, processes, routing.
I. Introduction
As we know whenever we planned the manufacturing system we consider the design criteria such as the system efficiency , the system will be efficient in all the way in production. All such criteria cannot be achieved untill the design production , planning scheduling and controlling steps work well. A FMS can be defined as production system consisting of identical multipurpose numerically controlled machine (work stations). FMS is a manufacturing system in which there is some amount of flexibility that allows the system to react in the case of changes. FMS works for automated material and tools handling system , load and unload stations, inspection stations , storage areas and a hierarchical control system. Generally when time is being planned , the objective is to design a system which will be efficient in the production of the entire range of parts. A FMS provides the efficiency of automated high- volume mass production. Scheduling in an FMS environment is more complex and difficult than in a conventional manufacturing environment. Scheduling of FMS determine an optimal schedule and controlling an FMS is considered as difficult task. Fuzzy set theory was introduced in 1965 by zadeh. Fuzzy logic approaches easily deal with uncertain and incomplete information and human experts, knowledge can be easily coded into fuzzy logic approaches for scheduling FMS is consider due to its ability to deal uncertain and incomplete information and with multi objective problem.
II. Review of Literature
2.1.JIPING NIU, JOHN DARTNALL.[1] gives the idea regarding fuzzy –mrp-ii deals with uncertantity and imprecision. Fuzzy –mrp –II shows all of the information for the decision makers allowing them to consider all possibilities of the orders.
2.2 SANJOY PETROVIC and CAROLE FAYAD[2] This paper deals with the load- balancing of m/c in a real-world job scheduling algorithm allocates jobs ,splits into lots on identical m/c with objectives to reduce job total throughput time and to improve m/c utilization. 2.3. RIPON KUMAR CHAKRABORETY AND MD.A.AKHTAR HASSEN.[3] This paper work demonstrated interactive fuzzy based genetic algorithmic approach solving a two products and two period aggregate production planning with some vulnerable managerial contraries like imprecise demands, variable manufacture cost etc… here the Author Employee different unique genetic algorithm parameters scrupulously for solving non deterministic Polynomials problem like app problems. 2.4 PARAMOT SRINOI,A/PROF. ABRAHIM SHAYAN, DR. FATMAEH GHOTB[4]. This paper present research project under taken as industrial institutes switchburne in the area of fuzzy scheduling. In this paper fuzzy based schedule model deal with the parts routing problem. Model with select best alternative route with multi criteria scheduling through an approach based on fuzzy logic. 2.5. DUSAN TEODORNIC.[5]. the paper represent classification and analysis the result achieved using fuzzy logic to model complex traffic and transportation process. fuzzy logic is shown to be very promising mathematically approach to modeling traffic and transportation process characterized by subjectivity, ambiguity, uncertainty and imprecision.
RESEARCH ARTICLE OPEN ACCESS
2. Miss. Ashwini. A. Mate Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 6), July 2014, pp.104-111
www.ijera.com 105 | P a g e
2.6 by MANISH AGRAWAL.[6] Here washing machine are common feature today Indian household. The most important utility customer can drive from washing machine. the paper represent idea of controlling the washing time using fuzzy logic control. The paper describes the produce that can be used to get the suitable time for different cloths. the process is based entirely on principle of taking no precise inputs From the sensor, subjecting them to fuzzy arithemats and obtaining crisp value of washing time. It is quite clear from the paper itself that this method can be used in practice to further automates the washing machine. Never the less, this method though with much larger number of inputs parameters and further complex situation is be used qty the giants like LG and Samsung. 2.7 ZIAUL HASSAN SERNEABAT, NABILA CHOUDHURY, DR. A.K.M.MASUD[7]. This paper gives the study of simulation of FMS.FMS is the production system consisting of identical multipurpose numerically controlled m/cs. Here the model prioritize the job and select the best alternative route with multi-criteria scheduling through an approach based on fuzzy logic and with the help of rules the sequence of the jobs are done and the best route is selected.
III. Fuzzy logic Approach to FMS
The present industrial trend of manufacturing low cost low-to-medium volumes of modular products with high variability demands manufacturing systems with flexibility and low delivery times. This lead to manufacturing systems with small batch productions, low setup times and many decisional degrees of freedom. The scheduling problem consists of several decisional points. A first division into three parts can be made: Timing: that is, when to insert a part into the system; Sequencing: that is, defining the order with which different parts (batches, orders) are inserted into the system; Routing: that is, defining the route (machine) for a part in presence of alternatives.
Fuzzy logic has the ability to simultaneously consider multiple criteria. Furthermore, the advantage of the fuzzy logic system approach is that it incorporates both numerical and linguistic variables. In this paper, we apply fuzzy logic to simulate FMS. The fuzzy based simulation, in this paper, is designed to solve the problem of determine the job sequence and selecting the best part route. In particular, we will show how to obtain the simulation via a proposed fuzzy model as shown in figure 1.
Fig. 1 Structure of a Fuzzy Logic System
IV. A CASE FOUND IN INDUSTRY
As the space wood is the furniture manufacturing industry ,here we found the various problem related scheduling after visiting the industry. For tackling the various problem we applying the fuzzy logic application to get the schedule for performing various operation in manufacturing unit. The Fuzzy scheduler considers two particular rules in the scheduling problem: Sequencing of job and routing. The sequencing of jobs was approached using fuzzy controllers having rules with two parameters (Processing time and, Due date) and one consequent.
The fuzzy system determine the route for each job loading in a machine , so that whenever the load station or the machine are free the job with the highest priority go through various operation. The decisional point that was considered is the routing problem, that is, the choice of one among many possible routes. In the problem considered this is equivalent to choosing the machine for next processing of a job, among the possible alternatives for that job The various operation done in industry:. 1-cutting 2-cnc operation 3-moulding 4-laying 5-sanding 6-glueing 7-foiling 8-inspection 9-packing The following assumptions on the Flexible Manufacturing System were made:
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1. Tool management is not considered, i.e. it is supposed that all the tools are available where needed. 2. Failure of workstations and/or transport systems is not considered, i.e., the machines and/or transport subsystem are not subject to failure. 3. Orders arrive to the FMS as Poisson processes with a fixed inter-arrival time. 4. Production of orders occurs in batches, and the movement of the whole batch is considered, so that batch dimensions are not important. 5. Setup times are independent of the order in which operations are executed, i.e. they are constant and embodied in the operation times of each job (batch). 6. There are as many pallets and fixtures as are needed (this assumption is mitigated by the fact that the number of jobs in the system is constantly controlled). 7. The routing of every job is random and directly defined as a sequence of workstations the job has to go through. Thus, the route of a job is not defined in terms of the operations needed by the job. In other words, every operation corresponds directly to the workstation that will execute it, i.e., the routing is defined as a sequence of workstations. 8. There can be multiple routing choices, i.e. at a certain point a job can be equivalently sent to different workstations (as specified in its routing plan) having different processing times. 9. Loading, unloading and processing times are random. 10. Due dates are assigned according to the total processing time of a job. 11. Each workstation can work only one job at a time. 12. The transport system is composed of fork lift truck and each fork lift truck can transport only one sheet at a time.
13. Neither the weight of a piece nor the dimension of a batch affects the speed of fork lift truck which is assumed to be constant.
14. Every workstation has one input buffer and no output buffer, therefore it will be free as soon as there is one free trolley that can transport the processed job to another workstation. 15. Delays in accessing the state information are neglected. 16. Among all the possible scheduling rules the following are considered: · Sequencing for a job (selection of a piece among those waiting to receive service from a machine); · Routing decisions concerning the next required workstation.
V. Problem Definition
When a manufacturing unit produce a product as per customer order. For production process they need schedule, planning. They schedule to placed product at right time. As problem found in industry is improper scheduling. There is no allocation of job at proper machine at proper time. When the job is available at the machine the other machine were idle and the due to this the productivity of the industry lack behind. As there are 4 CNC machine which are fully automated as program feed to the machine they work but after completion of one job the machine were idle and this cause the less productivity. To reduce the such kind of problem this model gave the proper schedule for every job.
The FMS described in this paper consists of 4 different CNC machining centers ,three panel saw with finite local buffer capacity, all capable of performing the required operations on each part type, a load/unload station and material handling system with a fork lift truck which can load one pallet at a time. The system produces two different part types, A and B as shown in Table 1. It is assumed that it takes 3 minutes to load and unload a part on a pallet at load/unload station. The time to cross the distance between two consecutive MCs is assumed to be 0.5 minute. The arrangement of the FMC hardware is shown in Figure 2.
Fig. 2 Diagram of the Case Study
Each machine is capable of performing different operations, but no machine can process more than one part at a time. Each part type has several alternative routings. Operations are
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not divided or interrupted when started. Set up times are independent of the job sequence and can be included in processing times. The scheduling problem is to decide the sequence of the jobs and which alternative routes should be selected for each job.
VI. The Fuzzy Based Model :
Proposed approach of this research is to identify different scheduling parameters such as, Processing time, for Job sequencing and processing time for routing and construct their membership functions and fuzzy rules. Using these membership functions and fuzzy rules a fuzzy interference system (FIS) is developed to identify the best route using MATLAB fuzzy logic toolbox. The variables are selected to identify the job, named, processing Time (PT),. All the variables are assigned with triangular membership function and divided into three zones: Small, Medium and High. The output of these
variables is priority varying from 0 to 1. The priority variable is also assigned with triangular membership function and divided into 9 portions. Minimum (MN), Negative Low (NL), Low (LO), Negative Average (NA), Average (AV), Positive Average (PA), High (HI), Positive High (PH) and Maximum (MX).The variable are selected to identify the best route, Processing Time (PT). All the variables are assigned with triangular membership function and divided into three zones : Small, Medium and High. The output of these variables is priority varying from 0 to 1. The priority variable is also assigned with triangular membership function and divided into 9 portions. Minimum (MN), Negative Low (NL), Low (LO), Negative Average (NA), Average (AV), Positive Average (PA), High (HI),
Positive High (PH) and Maximum (MX).
Fig a
Fig b
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Fig c
Fig d
Fig e
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Fig f Fig. Membership functions of fuzzy input variables
In case of route selection, the variables of processing time, Similar to job sequencing, the total number of possible ordered pairs of these states is 27 and for each of these ordered pairs of states, we have to determine and appropriate state of variable route priority. The decision table is given below: Inference Rules for Route Selection using two Inputs and One Output The route priority criteria now used to derive fuzzy inference rules shown as an example: 1. If (Processing Time is Small) then (Route Priority is Maximum) .......... 27. If (Processing Time is High) then (Route Priority is Minimum)
VII. The experiment and Result
Two jobs are considered here with different processing times, due dates. They are determined based on customer requirements and the cost of the raw materials needed to finish the jobs. Processing time here is the ideal time, means time needed if it was machined in just one machine. The overall system comprises 4 different CNC machining centers (MCs), all capable of performing the required operations on each part type, a load/unload station and material handling system with one fork lift truck which can carry one pallet at a time. The system produces two different part types, A, B . It is assumed that it takes 3 minutes to load and unload a part on a pallet at load/unload station. Processing time for Job A - 11.96 hrs
processing time for job B -11.86.hrs
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Fig for job B
Fig for job A
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Routes obtained: Job A: 1-1-3-4-5 1-2-3-4-5 1-3-3-4-5 1-4-3-4-5 2-1-3-4-5 2-2-3-4-5 2-3-3-4-5 2-4-3-4-5 3-1-3-4-5 3-2-3-4-5 3-3-3-4-5 3-4-3-4-5 FOR JOB B: 1-1-3-4-5 1-2-3-4-5 1-3-3-4-5 1-4-3-4-5 2-1-3-4-5 2-2-3-4-5 2-3-3-4-5 2-4-3-4-5 3-1-3-4-5 3-2-3-4-5 3-3-3-4-5 3-4-3-4-5 Routes obtained by fuzzy model
VIII. Conclusion and Recommendation
The work presented in this paper was directed towards investigating the applicability of fuzzy techniques as a decision aid in the short-term control of flexible manufacturing systems. For this purpose a flexible manufacturing system for two jobs composed of four machines, one fork lift truck, one load and one unload station and with routings and arrivals with fixed statistical characteristics was considered. A fuzzy scheduler for job sequencing and routing was developed. This scheduler uses fuzzy logic systems as well as fuzzy multiple attribute decision-making techniques. The thesis was done to increase performance by using fuzzy techniques and also in giving a systematic design procedure that takes into account multiple objectives and needs no interface with linguistic directions from human experts. In this research, job A having the first priority and routing.. Again, only job priority and routing are taken into account, some other criteria‟s can also be added. Several parameters are used to design the problem, but, yet there may be other parameters which can be added to make the model more accurate. Here, triangular membership functions were
used. There are some other membership functions which could give different results. All possible rules are taken, but if more parameters were added, number of the rules would have been increased. All this changes may lead the model to better results.
Reference
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