Design and Implementation of Discrete Augmented Ziegler-Nichols PID ControllerIDES Editor
ย
Although designing and tuning a proportionalintegral-
derivative (PID) controller appears to be conceptually
intuitive, but it can be hard in practice, if multiple (and often
conflicting) objectives such as short transient and high
stability are to be achieved. Traditionally Ziegler Nichols is
widely accepted PID tuning method but itโs performance is
not accepted for systems where precise control is required. To
overcome this problem, the online gain updating method
Augmented Ziegler-Nichols PID (AZNPID) was proposed, with
the amelioration of Ziegler-Nichols PIDโs (ZNPIDโs) tuning
rule. This study is further extension of [1] for making the
scheme more generalized. With the help of fourth order
Runge-Kutta method, differential equations involved in PID
are solved which significantly improves transient performance
of AZNPID compared to ZNPID. The proposed augmented
ZNPID (AZNPID) is tested on various types of linear processes
and shows improved performance over ZNPID. The results of
the proposed scheme is validated by simulation and also
verified experimentally by implementing on Quanserโs real
time servo-based position control system SRV-02.
Modified sub-gradient based combined objective technique and evolutionary pro...IJECEIAES
ย
A security constrained non-convex power dispatch problem with prohibited operation zones and ramp rates is formulated and solved using an iterative solution method based on the feasible modified sub-gradient algorithm (FMSG). Since the cost function, all equality and inequality constraints in the nonlinear optimization model are written in terms of the bus voltage magnitudes, phase angles, off-nominal tap settings, and the Susceptance values of static VAR (SVAR) systems, they can be taken as independent variables. The actual power system loss is included in the current approach and the load flow equations are inserted into the model as the equality constraints. The proposed modified sub gradient based combined objective technique and evolutionary programming approach (MSGBCAEP) with ํ as decision variable and cost function as fitness function is tested on the IEEE 30-bus 6 generator test case system. The absence of crossover operation and adoption of fast judicious modifications in initialization of parent population, offspring generation and normal distribution curve selection in EP enables the proposed MSGBCAEP approach to ascertain global optimal solution for cost of generation and emission level.
Phenomenological Decomposition Heuristics for Process Design Synthesis of Oil...Alkis Vazacopoulos
ย
The processing of a raw material is a phenomenon that varies its quantity and quality along a specific network and logics and logistics to transform it into final products. To capture the production framework in a mathematical programming model, a full space formulation integrating discrete design variables and quantity-quality relations gives rise to large scale non-convex mixed-integer nonlinear models, which are often difficult to solve. In order to overcome this problem, we propose a phenomenological decomposition heuristic to solve separately in a first stage the quantity and logic variables in a mixed-integer linear model, and in a second stage the quantity and quality variables in a nonlinear programming formulation. By considering different fuel demand scenarios, the problem becomes a two-stage stochastic programming model, where nonlinear models for each demand scenario are iteratively restricted by the process design results. Two examples demonstrate the tailor-made decomposition scheme to construct the complex oil-refinery process design in a quantitative manner.
Currently, distributed cyber-physical systems (CPS) rely upon embedded real-time systems, which can guarantee compliance with time constraints. CPS are increasingly required to act and interact with one another in dynamic environments. In the last decades, the Belief-Desire-Intention (BDI) architecture has proven to be ideal for developing agents with flexible behavior. However, current BDI models can only reason about time and not in time. This lack prevents BDI agents from being adopted in designing CPS, and particularly in safety-critical applications. This paper proposes a revision of the BDI model by integrating real-time mechanisms into the reasoning cycle of the agent. By doing so, the BDI agent can make decisions and execute plans ensuring compliance with strict timing constraints also in dynamic environments, where unpredictable events may occur.
Video presentation: https://youtu.be/X6S74JVsFOU
Manufacture of a Biodegradable Detergent on Small ScaleCSCJournals
ย
This paper deals with an aggregate planning for a small scale production unit using a network flow model for full utilization of its capacity to meet the changing forecasted demand .The formulation of the problem is done by using the given inventory capacity with backorders by making a trade-off among inventory costs , backlog costs, production and subcontracting costs. The total cost function and the constraint inequalities were developed assuming the cost functions to be linear. The parameters of objective function and the constraints were estimated from the economics of the plant. The values of the work force, overtime, backlog, amount subcontracted were determined for a planning horizon of six months using an LP computer package. This method of production scheduling took care of the fluctuating demand utilizing the full capacity of the plant.
Procurement Strategy for Manufacturing and JITIJERD Editor
ย
Procurement involves the purchase of goods and services from the suppliers for the manufacturing units. Procuring the items in the most optimized way is very much desired to implement JIT effectively. Manufacturer-supplier relationship is very crucial for effective procurement policy. The present paper deals with various procurement strategies of manufacturing that include the optimization of manufacturing quantity along with the procurement of multiple input items. The procurement cycles for input items are considered in small lot sizes, which are essential for the effective implementation of JIT. The method of integer programming has been used to find the optimum integer values of number of orders for procuring the input items, which is usually found to be in fraction for a real manufacturing environment.
Malmquist Total Factor Productivity Index for Modeling Dairy SectorARNAB ROY
ย
Productivity growth in agriculture sector is considered important to the development process, allowing countries to produce more food at lower cost, improve nutrition and welfare, and release resources to other sectors. The Total Factor Productivity (TFP) growth, traditionally calculated as the ratio of total output to the weighted sum of inputs, is quite often interpreted as a shift of the production function.TFP represents the increase in total production which is in excess of the increase that results from increase in inputs. It results from intangible factors such as technological change, education, research and development, synergies, etc. the Malmquist index, a data envelopment analysis-type nonparametric technique, to decompose productivity growth into technical efficiency and technological change for Indian dairy sector. The results indicate that the increase in dairy productivity is mainly attributed to the increase in technical change, and the efficiency gain found is largely the result of improvements in scale efficiency.
Fall 2016 Insurance Case Study โ Finance 360Loss ControlLoss.docxlmelaine
ย
Fall 2016 Insurance Case Study โ Finance 360
Loss Control
Loss control activities of a business focus on finding and implementing solutions to reduce the probability of loss (loss prevention) and/or reduce the actual amount of loss (loss reduction), and therefore reduce the total cost of risk to maximize firm profitability.
Loss control techniques have been widely used in environmental loss prevention, catastrophic loss prevention, and employee-related risk management. Many firms face loss exposures caused by using, storing, and transporting hazardous materials, caustic substances, gasses, acids, etc., and may have unique issues posed by deployment of โgreenerโ vehicle fleets using CNG, LNG, and bio-fuel solutions. Catastrophic risks, such as earthquakes, tornado, hurricanes or big fire, also pose significant threat to the property safety and business continuation for firms. Employee behavior-related risks and product safety are also important concern of corporate risk management.
Lack of effective loss control (such as inadequate systems, inadequate standards, and inadequate compliance with safety standards) may cause significant damage to a firm, such as injury costs, property damage, liability damage, bad press, lower sales, loss of employee morale, so on and so forth, as British Petroleum (BP) or Toyota had suffered in the past.
In this project, select an S&P 500 company and analyze its loss control policies focusing on either environmental loss prevention, or catastrophic loss prevention, or employee-related risk management.
Your analysis should address the following questions in the least:
ยท How likely the firm is subject to catastrophic losses?
ยท Has the business suffered losses of the kind in the past?
ยท What losses could be caused to the firm if a catastrophic event occurs?
A. Direct Property Loss
B. Indirect (or consequential) Property Loss
C. Liability Loss
D. Personnel Loss
E. Crime
F. Other Loss Exposures
ยท What loss control activities has the firm implemented to reduce the loss?
ยท E.g. For Property loss control, comment on Facility design and construction, Automatic Sprinkler Protection, Preventative maintenance, Equipment and Process controls and safeguards, Human Element programs, Pre-incident planning and Business continuity planning
ยท Proactive Safety procedures vs. Reactive Safety & Recovery policies
Requirements
1. Paper length: 8 page minimum, 12 page maximum; 12 point fontโdouble-spaced
2. Paper sections
A. Title Page, including: (1) paper title, (2) course number and name, (3) instructor, (4) your name, and (5) date submitted
B. Executive Summary: This is a 1-2 paragraph overall summary of your paper.
C. Discussion and analysis: Cover all the individual topic areas set out above, each of which should be labeled with an appropriate subject heading.
D. Works Cited: List all secondary sources consulted in preparing this paper.
E. Attachments (if any). You may append any relevant attachment to ...
Design and Implementation of Discrete Augmented Ziegler-Nichols PID ControllerIDES Editor
ย
Although designing and tuning a proportionalintegral-
derivative (PID) controller appears to be conceptually
intuitive, but it can be hard in practice, if multiple (and often
conflicting) objectives such as short transient and high
stability are to be achieved. Traditionally Ziegler Nichols is
widely accepted PID tuning method but itโs performance is
not accepted for systems where precise control is required. To
overcome this problem, the online gain updating method
Augmented Ziegler-Nichols PID (AZNPID) was proposed, with
the amelioration of Ziegler-Nichols PIDโs (ZNPIDโs) tuning
rule. This study is further extension of [1] for making the
scheme more generalized. With the help of fourth order
Runge-Kutta method, differential equations involved in PID
are solved which significantly improves transient performance
of AZNPID compared to ZNPID. The proposed augmented
ZNPID (AZNPID) is tested on various types of linear processes
and shows improved performance over ZNPID. The results of
the proposed scheme is validated by simulation and also
verified experimentally by implementing on Quanserโs real
time servo-based position control system SRV-02.
Modified sub-gradient based combined objective technique and evolutionary pro...IJECEIAES
ย
A security constrained non-convex power dispatch problem with prohibited operation zones and ramp rates is formulated and solved using an iterative solution method based on the feasible modified sub-gradient algorithm (FMSG). Since the cost function, all equality and inequality constraints in the nonlinear optimization model are written in terms of the bus voltage magnitudes, phase angles, off-nominal tap settings, and the Susceptance values of static VAR (SVAR) systems, they can be taken as independent variables. The actual power system loss is included in the current approach and the load flow equations are inserted into the model as the equality constraints. The proposed modified sub gradient based combined objective technique and evolutionary programming approach (MSGBCAEP) with ํ as decision variable and cost function as fitness function is tested on the IEEE 30-bus 6 generator test case system. The absence of crossover operation and adoption of fast judicious modifications in initialization of parent population, offspring generation and normal distribution curve selection in EP enables the proposed MSGBCAEP approach to ascertain global optimal solution for cost of generation and emission level.
Phenomenological Decomposition Heuristics for Process Design Synthesis of Oil...Alkis Vazacopoulos
ย
The processing of a raw material is a phenomenon that varies its quantity and quality along a specific network and logics and logistics to transform it into final products. To capture the production framework in a mathematical programming model, a full space formulation integrating discrete design variables and quantity-quality relations gives rise to large scale non-convex mixed-integer nonlinear models, which are often difficult to solve. In order to overcome this problem, we propose a phenomenological decomposition heuristic to solve separately in a first stage the quantity and logic variables in a mixed-integer linear model, and in a second stage the quantity and quality variables in a nonlinear programming formulation. By considering different fuel demand scenarios, the problem becomes a two-stage stochastic programming model, where nonlinear models for each demand scenario are iteratively restricted by the process design results. Two examples demonstrate the tailor-made decomposition scheme to construct the complex oil-refinery process design in a quantitative manner.
Currently, distributed cyber-physical systems (CPS) rely upon embedded real-time systems, which can guarantee compliance with time constraints. CPS are increasingly required to act and interact with one another in dynamic environments. In the last decades, the Belief-Desire-Intention (BDI) architecture has proven to be ideal for developing agents with flexible behavior. However, current BDI models can only reason about time and not in time. This lack prevents BDI agents from being adopted in designing CPS, and particularly in safety-critical applications. This paper proposes a revision of the BDI model by integrating real-time mechanisms into the reasoning cycle of the agent. By doing so, the BDI agent can make decisions and execute plans ensuring compliance with strict timing constraints also in dynamic environments, where unpredictable events may occur.
Video presentation: https://youtu.be/X6S74JVsFOU
Manufacture of a Biodegradable Detergent on Small ScaleCSCJournals
ย
This paper deals with an aggregate planning for a small scale production unit using a network flow model for full utilization of its capacity to meet the changing forecasted demand .The formulation of the problem is done by using the given inventory capacity with backorders by making a trade-off among inventory costs , backlog costs, production and subcontracting costs. The total cost function and the constraint inequalities were developed assuming the cost functions to be linear. The parameters of objective function and the constraints were estimated from the economics of the plant. The values of the work force, overtime, backlog, amount subcontracted were determined for a planning horizon of six months using an LP computer package. This method of production scheduling took care of the fluctuating demand utilizing the full capacity of the plant.
Procurement Strategy for Manufacturing and JITIJERD Editor
ย
Procurement involves the purchase of goods and services from the suppliers for the manufacturing units. Procuring the items in the most optimized way is very much desired to implement JIT effectively. Manufacturer-supplier relationship is very crucial for effective procurement policy. The present paper deals with various procurement strategies of manufacturing that include the optimization of manufacturing quantity along with the procurement of multiple input items. The procurement cycles for input items are considered in small lot sizes, which are essential for the effective implementation of JIT. The method of integer programming has been used to find the optimum integer values of number of orders for procuring the input items, which is usually found to be in fraction for a real manufacturing environment.
Malmquist Total Factor Productivity Index for Modeling Dairy SectorARNAB ROY
ย
Productivity growth in agriculture sector is considered important to the development process, allowing countries to produce more food at lower cost, improve nutrition and welfare, and release resources to other sectors. The Total Factor Productivity (TFP) growth, traditionally calculated as the ratio of total output to the weighted sum of inputs, is quite often interpreted as a shift of the production function.TFP represents the increase in total production which is in excess of the increase that results from increase in inputs. It results from intangible factors such as technological change, education, research and development, synergies, etc. the Malmquist index, a data envelopment analysis-type nonparametric technique, to decompose productivity growth into technical efficiency and technological change for Indian dairy sector. The results indicate that the increase in dairy productivity is mainly attributed to the increase in technical change, and the efficiency gain found is largely the result of improvements in scale efficiency.
Fall 2016 Insurance Case Study โ Finance 360Loss ControlLoss.docxlmelaine
ย
Fall 2016 Insurance Case Study โ Finance 360
Loss Control
Loss control activities of a business focus on finding and implementing solutions to reduce the probability of loss (loss prevention) and/or reduce the actual amount of loss (loss reduction), and therefore reduce the total cost of risk to maximize firm profitability.
Loss control techniques have been widely used in environmental loss prevention, catastrophic loss prevention, and employee-related risk management. Many firms face loss exposures caused by using, storing, and transporting hazardous materials, caustic substances, gasses, acids, etc., and may have unique issues posed by deployment of โgreenerโ vehicle fleets using CNG, LNG, and bio-fuel solutions. Catastrophic risks, such as earthquakes, tornado, hurricanes or big fire, also pose significant threat to the property safety and business continuation for firms. Employee behavior-related risks and product safety are also important concern of corporate risk management.
Lack of effective loss control (such as inadequate systems, inadequate standards, and inadequate compliance with safety standards) may cause significant damage to a firm, such as injury costs, property damage, liability damage, bad press, lower sales, loss of employee morale, so on and so forth, as British Petroleum (BP) or Toyota had suffered in the past.
In this project, select an S&P 500 company and analyze its loss control policies focusing on either environmental loss prevention, or catastrophic loss prevention, or employee-related risk management.
Your analysis should address the following questions in the least:
ยท How likely the firm is subject to catastrophic losses?
ยท Has the business suffered losses of the kind in the past?
ยท What losses could be caused to the firm if a catastrophic event occurs?
A. Direct Property Loss
B. Indirect (or consequential) Property Loss
C. Liability Loss
D. Personnel Loss
E. Crime
F. Other Loss Exposures
ยท What loss control activities has the firm implemented to reduce the loss?
ยท E.g. For Property loss control, comment on Facility design and construction, Automatic Sprinkler Protection, Preventative maintenance, Equipment and Process controls and safeguards, Human Element programs, Pre-incident planning and Business continuity planning
ยท Proactive Safety procedures vs. Reactive Safety & Recovery policies
Requirements
1. Paper length: 8 page minimum, 12 page maximum; 12 point fontโdouble-spaced
2. Paper sections
A. Title Page, including: (1) paper title, (2) course number and name, (3) instructor, (4) your name, and (5) date submitted
B. Executive Summary: This is a 1-2 paragraph overall summary of your paper.
C. Discussion and analysis: Cover all the individual topic areas set out above, each of which should be labeled with an appropriate subject heading.
D. Works Cited: List all secondary sources consulted in preparing this paper.
E. Attachments (if any). You may append any relevant attachment to ...
1. Which of the following is INCORRECT regarding the process capab.docxjackiewalcutt
ย
1. Which of the following is INCORRECT regarding the process capability index Cpk
Productivity can be improved by
Increasing inputs while holding outputs steady
Decreasing outputs while holding inputs steady
Increasing inputs and outputs in the same proportion
Increasing outputs while holding inputs steady
2. Productivity can be improved by
Increasing inputs while holding outputs steady
Decreasing outputs while holding inputs steady
Increasing inputs and outputs in the same proportion
Increasing outputs while holding inputs steady
3. Which of the following statements is INCORRECT regarding critical paths?
The path that takes the longest time to complete in a project is the critical path.
Activities on the critical path must have zero slack time.
Some non-critical activities may have zero slack time.
For any project, the (expected) project completion time is equal to the (expected) time duration of the projectโs critical path.
4. Suppose a project team has arrived at the following time estimates for an activity: a = 4 days, m = 6 days, and b = 8 days. What is the variance involved in this activity?
0.111
0.250
0.444
0.694
5. Suppose you are asked to determine the Lower Control Limit for a p-chart for quality control purposes. Samples are taken from the production line. The fraction defective is 0.008 and the standard deviation is 0.002 based on the samples. Set z = 3. Which of the following is the LCL of the p-chart?
0.001
0.002
0.006
0.013
6. The least squares method is to find out the intercept and the slope of a regression line that minimizes the sum of the squared differences between
observed values of the independent variable and predicted values of the independent variable
observed values of the independent variable and predicted values of the dependent variable
observed values of the dependent variable and predicted values of the dependent variable
None of the three is correct.
7. Which of the following statements is INCORRECT regarding corporate missions?
They reflect a company's purpose.
They indicate what a company intends to contribute to society.
They are formulated after strategies are known.
They define a company's reason for existence.
8. Given forecast errors of -2, 5, 10, and -3, what is the mean absolute deviation (MAD)?
2.5
3
4
5
9. Which of the following best describes the process focus strategy?
Appropriate for high-volume, low-variety production
Equipment or processes are arranged based on the progressive steps by which a product is made.
Also known as flow shop
Appropriate for low-volume, high-variety production
10. According to the definition of design quality,
Quality is the degree of excellence at an acceptable price
Quality depends on how well the product fits consumer preferences
Even though quality cannot be defined, you know what it is
Quality is the degree to which a specific product conforms to design specifications
11. Which of the f ...
Planning of Supply when lead time uncertain: trade-off between holding cost a...ijsrd.com
ย
A supply planning for two-level assembly systems under lead-time uncertainties is considered. It is supposed that the demand for the finished product and its due date are known. It is assumed also that the component lead-time at each level is a random discrete variable. The objective is to find the release dates for the components at level two in order to minimize the expected component holding costs and to maximize the customer service level for the finished pr
Scalable frequent itemset mining using heterogeneous computing par apriori a...ijdpsjournal
ย
Association Rule mining is one of the dominant tasks of data mining, which concerns in finding frequent
itemsets in large volumes of data in order to produce summarized models of mined rules. These models are
extended to generate association rules in various applications such as e-commerce, bio-informatics,
associations between image contents and non image features, analysis of effectiveness of sales and retail
industry, etc. In the vast increasing databases, the major challenge is the frequent itemsets mining in a
very short period of time. In the case of increasing data, the time taken to process the data should be
almost constant. Since high performance computing has many processors, and many cores, consistent runtime
performance for such very large databases on association rules mining is achieved. We, therefore,
must rely on high performance parallel and/or distributed computing. In literature survey, we have studied
the sequential Apriori algorithms and identified the fundamental problems in sequential environment and
parallel environment. In our proposed ParApriori, we have proposed parallel algorithm for GPGPU, and
we have also done the results analysis of our GPU parallel algorithm. We find that proposed algorithm
improved the computing time, consistency in performance over the increasing load. The empirical analysis
of the algorithm also shows that efficiency and scalability is verified over the series of datasets
experimented on many core GPU platform.
Planning and Scheduling of a Corrugated Cardboard Manufacturing Process in IoTijtsrd
ย
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
Similar to Quantitative approach for theory of constraints in manufacturing (20)
Business Valuation Principles for EntrepreneursBen Wann
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This insightful presentation is designed to equip entrepreneurs with the essential knowledge and tools needed to accurately value their businesses. Understanding business valuation is crucial for making informed decisions, whether you're seeking investment, planning to sell, or simply want to gauge your company's worth.
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
Skye Residences | Extended Stay Residences Near Toronto Airportmarketingjdass
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Memorandum Of Association Constitution of Company.pptseri bangash
ย
www.seribangash.com
A Memorandum of Association (MOA) is a legal document that outlines the fundamental principles and objectives upon which a company operates. It serves as the company's charter or constitution and defines the scope of its activities. Here's a detailed note on the MOA:
Contents of Memorandum of Association:
Name Clause: This clause states the name of the company, which should end with words like "Limited" or "Ltd." for a public limited company and "Private Limited" or "Pvt. Ltd." for a private limited company.
https://seribangash.com/article-of-association-is-legal-doc-of-company/
Registered Office Clause: It specifies the location where the company's registered office is situated. This office is where all official communications and notices are sent.
Objective Clause: This clause delineates the main objectives for which the company is formed. It's important to define these objectives clearly, as the company cannot undertake activities beyond those mentioned in this clause.
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Liability Clause: It outlines the extent of liability of the company's members. In the case of companies limited by shares, the liability of members is limited to the amount unpaid on their shares. For companies limited by guarantee, members' liability is limited to the amount they undertake to contribute if the company is wound up.
https://seribangash.com/promotors-is-person-conceived-formation-company/
Capital Clause: This clause specifies the authorized capital of the company, i.e., the maximum amount of share capital the company is authorized to issue. It also mentions the division of this capital into shares and their respective nominal value.
Association Clause: It simply states that the subscribers wish to form a company and agree to become members of it, in accordance with the terms of the MOA.
Importance of Memorandum of Association:
Legal Requirement: The MOA is a legal requirement for the formation of a company. It must be filed with the Registrar of Companies during the incorporation process.
Constitutional Document: It serves as the company's constitutional document, defining its scope, powers, and limitations.
Protection of Members: It protects the interests of the company's members by clearly defining the objectives and limiting their liability.
External Communication: It provides clarity to external parties, such as investors, creditors, and regulatory authorities, regarding the company's objectives and powers.
https://seribangash.com/difference-public-and-private-company-law/
Binding Authority: The company and its members are bound by the provisions of the MOA. Any action taken beyond its scope may be considered ultra vires (beyond the powers) of the company and therefore void.
Amendment of MOA:
While the MOA lays down the company's fundamental principles, it is not entirely immutable. It can be amended, but only under specific circumstances and in compliance with legal procedures. Amendments typically require shareholder
The world of search engine optimization (SEO) is buzzing with discussions after Google confirmed that around 2,500 leaked internal documents related to its Search feature are indeed authentic. The revelation has sparked significant concerns within the SEO community. The leaked documents were initially reported by SEO experts Rand Fishkin and Mike King, igniting widespread analysis and discourse. For More Info:- https://news.arihantwebtech.com/search-disrupted-googles-leaked-documents-rock-the-seo-world/
Taurus Zodiac Sign_ Personality Traits and Sign Dates.pptxmy Pandit
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Explore the world of the Taurus zodiac sign. Learn about their stability, determination, and appreciation for beauty. Discover how Taureans' grounded nature and hardworking mindset define their unique personality.
Premium MEAN Stack Development Solutions for Modern BusinessesSynapseIndia
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Stay ahead of the curve with our premium MEAN Stack Development Solutions. Our expert developers utilize MongoDB, Express.js, AngularJS, and Node.js to create modern and responsive web applications. Trust us for cutting-edge solutions that drive your business growth and success.
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๐๐ ๐๐จ๐ฆ๐ฌ (๐๐ ๐๐จ๐ฆ๐ฆ๐ฎ๐ง๐ข๐๐๐ญ๐ข๐จ๐ง๐ฌ) is a professional event agency that includes experts in the event-organizing market in Vietnam, Korea, and ASEAN countries. We provide unlimited types of events from Music concerts, Fan meetings, and Culture festivals to Corporate events, Internal company events, Golf tournaments, MICE events, and Exhibitions.
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โขCHILDREN ART EXHIBITION 2024: BEYOND BARRIERS
โข WOW K-Music Festival 2023
โข Winner [CROSS] Tour in HCM
โข Super Show 9 in HCM with Super Junior
โข HCMC - Gyeongsangbuk-do Culture and Tourism Festival
โข Korean Vietnam Partnership - Fair with LG
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Quantitative approach for theory of constraints in manufacturing
1. Mathematical Theory and Modeling www.iiste.org
ISSN 2224-5804 (Paper) ISSN 2225-0522 (Online)
Vol.2, No.2, 2012
Quantitative approach for Theory of Constraints in
Manufacturing
Bharat Chede1*, Dr C.K.Jain2, Dr S.K.Jain3, Aparna Chede4
1. Reader, Department of Mechanical Engineering, Mahakal Institute of Technology and Management,
Ujjain
2. Ex-Principal, Ujjain Engineering College, Ujjain
3. Principal, Ujjain Engineering College, Ujjain
4. Lecturer, Department of Mechanical Engineering, Mahakal Institute of Technology and Science, Ujjain
* Email of the corresponding author : bharat_chede@rediffmail.com
Abstract
In this paper, a systematic and quantitative view is presented for the application of the theory of
constraints in manufacturing. This is done employing the operational research technique of mathematical
programming. The potential of the theory of constraints in manufacturing is demonstrated. By applying
the TOC philosophy based on this information, managers will be able to take the right actions that will
improve the profitability of their companies. The model is proposed to be used with the TOC philosophy
in order to improve the financial performance of a company.
Keywords: Theory of Constraints, bottlenecks, Capacity-constrained resources (CCR), Throughput
1. Introduction
The Constraints resource manufacturing organizing encounter very often the situation of surplus demand
that its capacity to manufacture, which is because of the company policy to grasp all the market demand in
order to prevent other major competitors from penetrating the market and at the same time maintains the
company reputation for on time delivery. Manufacturing has undergone a number of changes in the last few
years, in view of the economic environment in which companies are operating and of the introduction of
advanced manufacturing technology. The model so prepared relates capacity constrained resources,
material cost, direct labour cost, availability of capital, selling price, demand.
2. Theory of constraints
Theory of constraints is management policy developed by E.M. Goldratt. It maintains a focus on system
constraints. Assumes the firm goal is to make money. Theory of constraints concept of measurement
system was conceived on three simple performance measures, namely Throughput, inventory and operating
expenses. Five steps of Theory of constraints are
2.1 Identify the system constraints.
2.2 Decide how to exploit system constraints.
2.3 Subordinate everything else to the above decision.
2.4 Elevate the system constraints.
2.5 Go back to step 1, do not allow inertia to be the constraint.
The Theory of Constraints, hereafter abbreviated as TOC, is a production and operations
management strategy centered on the concept of capacity-constrained resources (CCR), more commonly
called bottlenecks. TOC starts from the assumption of the existence of one or more CCR in any system.
This assumption tends to lose its validity in systems with balanced loads. The performance may be profit,
production volume, or any other suitable criterion. A simple example of a CCR is the slowest operation in a
continuous simple flow line of production of discrete parts. The implementation of TOC in practice is
achieved in a sequence of logical steps;
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2. Mathematical Theory and Modeling www.iiste.org
ISSN 2224-5804 (Paper) ISSN 2225-0522 (Online)
Vol.2, No.2, 2012
1. CCR Identification
2. CCR Management
3. Performance Improvement
3. CCR Identification
A CCR is defined as a resource which prevents the system from achieving a higher level of performance. It
is then necessary to define precisely a metric for performance. In TOC, as it is applied in manufacturing
environments, performance is considered to be profit which is defined as
PROFIT = THROUGPUT โ OPERATING EXPENSES,
In turn, Throughput is defined as the sale prices of finished products, and Operating Expenses are defined
as the costs of raw materials employed in obtaining these finished products.
Assuming that a manufacturing facility such as a workshop can make a number of several finished
products, each with its unit sale price, unit raw material costs, and market demand, then maximum profit is
obtained by making the most profitable mix of finished products subject to multi-resource capacities
available. A CCR is defined as the resource which has the highest ratio of utilization to availability. Now
we develop a linear programming (LP) model for CCR identification in manufacturing systems by
introducing necessary notation.
i โ index denoting part; i = 1,โฆ,I
j โ index denoting resource; j = 1,โฆ,J
Aij โ unit i processing time of part i in resource j
Bi โ unit profit of part i
Cj โ capacity of resource j in planning horizon
Di โ market demand for part i in planning horizon
Ri โ amount produced of part i in planning horizon
Sj โ idle time of resource j in planning horizon
The LP model for CCR identification may be set down as:
I
Maximise โ Bi ร Ri (1)
i=1
The objective function (1) represents the total profit obtained over the planning horizon.
Subject to
I
โ Aij + Sj = Cj j = 1 โฆ.J (2)
i=1
The constraints (2) ensure the capacity limit for each resource j.
Ri โค Di i = 1 โฆ. I (3)
The constraints (3) ensure that production of each part does not exceed demand.
Ri โฅ 0 i = 1 โฆ. I (4)
Sj โฅ 0 j = 1 โฆ. J (5)
Finally, the constraints (4) and (5) guarantee the no negativity of the decision variables R i and Sj of the LP
model, whose input parameters consist of the set Aij, Bi, and Ci. The resource with the highest ratio of
utilization to availability, Cj, is the same as the resource with the minimum idle time, S j. Consequently, any
resource with Sj = 0 is a CCR. It can be seen that the LP model seeks to identify the optimum part mix and
the CCR (s) in the manufacturing system. The LP model provides the master production schedule which
maximizes Throughput.
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3. Mathematical Theory and Modeling www.iiste.org
ISSN 2224-5804 (Paper) ISSN 2225-0522 (Online)
Vol.2, No.2, 2012
I
โ Aij ร Ri (6)
i=1
4.CCR Management
Once identified, a CCR must be used effectively in such a way so as to obtain the desired performance of
the manufacturing system. This is known as CCR management, which is implemented by a scheduling
technique referred to as drum-buffer-rope (DBR). DBR reduces this complexity by focusing attention on
CCRs as opposed to all resources. In order to achieve the highest performance possible, CCRs must be
scheduled with a view to avoiding unnecessary idle time which implies lost throughput.
1. Each task/activity happens only once.
2. Precedence among tasks/activities is specified explicitly than through the nature and amounts of material
movement between tasks/activities. These two limitations are removed by employing the state task network
(STN) representation.
5. STN โ DBR Scheduling
Before developing the model, we introduce necessary notation
i = index denoting task; i=1,โฆ,I Cs = maximum storage capacity dedicated to state S
j = index denoting production unit; j=1,โฆJ Ij = Set of tasks which can be performed by production unit j
t = index denoting time; t=1,โฆH = maximum capacity of production unit j when used
for performing task i
s = index denoting material state; s=1,โฆS = minimum capacity of production unit j when used for
performing task i
Si = set of states which has task i as input Wijt = binary decision variable = 1 if production unit j starts
processing task j at the start of period t ; = 0 otherwise
= set of states which has task i as output Bijt = amount of material which starts undergoing task i in
production unit j at the start of period t
ฯis = proportion of input of task i from state S ะ Si Sst = amount of material stored in state S at the start of period
t
= Proportion of output of task i to state S ะ Si M = sufficiently large number
Pis = processing time for output of task i to Fsjt = amount of material of state s being held in production
during the tome interval t
Pi = completion time of task i, B = index denoting buffer unit
Ki = set of production units capable of performing C = index denoting CCR unit
task
Ts = set of tasks which has input from state S Fs = set of states whose members are finished products
= set of tasks which has output to state S Rst = quantity of finished products in state S scheduled for
delivery at time t
The STN model for DBR scheduling may then be set down as:
Minimise
(7)
t (8)
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4. Mathematical Theory and Modeling www.iiste.org
ISSN 2224-5804 (Paper) ISSN 2225-0522 (Online)
Vol.2, No.2, 2012
t (9)
t, , (10)
t, , (11)
0 t, (12)
Sst = Ss, i-1 + (13)
(14)
(15)
(16)
(17)
In the objective function (7), we seek to minimize the maximum difference between delivered quantities
and stored finished products.
The constraints (8) ensure that at any given time, a production unit which is not a CCR can only start at
most one task. For a CCR, the constraints (9) guarantee that it is never idle, since by definition a CCR is the
resource that sets an upper limit to manufacturing system performance. The constraints (10) serve to ensure
that tasks are performed non-preemptively. The constraints (11) ensure that the quantity of material
undergoing a task in a production unit is bounded by the minimum and maximum capacities of that unit.
The constraints (12) guarantee that the quantity of material stored in a state does not exceed the maximum
storage capacity for that state. The constraints (13) and (14) constitute material balances for production
units and buffers, respectively. The binarity and non-negativity of the appropriate decision variables are
ensured by the constraints (15)-(17).
In the STN model, we have assumed that the only unit possessing an input buffer is a CCR. Neither setup
non maintenance tasks are taken into consideration. At the same time, we note that all the aforementioned
aspects can be easily incorporated into a more general STN model. We purposely restricted our scope so as
to focus on the attainment of scheduled deliveries of finished products.
6. Performance Improvement
The identification and management of CCRs serve to achieve maximum performance for given capacity
and demand levels. In order to go beyond this level of performance, measures have to be taken and the
corresponding investments have to be made to increase capacity and/or demand.
6.1- Throughput (TH) defined as the rate at which the manufacturing system generates revenue.
6.2- Inventory (IN) defined as the investment made to generate revenue.
6.3- Operating expense (OE) defined the cost of transforming inventory into throughput.
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5. Mathematical Theory and Modeling www.iiste.org
ISSN 2224-5804 (Paper) ISSN 2225-0522 (Online)
Vol.2, No.2, 2012
In the context of TOC, system performance is improved by increasing inventory in order to increase
throughput and/or decrease operating expense. It is clear that the performance measurements of TOC are
very different from traditional management accounting approaches.
Apart from external constraints, such as market demand, internal CCRs by definition limit the performance
of manufacturing system. Consequently, CCRs must be the focus of all improvement efforts. For a CCR
machine, its capacity may be increased by such measures as setup reduction, breakdown reduction, and
processing speed enhancement. All such measures naturally involve investments.
7. Case Study
A manufacturing organization considered in this article is based nearby the capital of India. Due to
sudden increase in export order from African countries, management had to decide on action plan. As
demand was uncertain to sustain management was not interested in strategic investment for resource
acquisition. After considering the entire related factor, management was not interested on providing
overtime also. Management was interested on outsourcing. Thus, the present study was conducted to
guide the management about outsourcing.
Company manufactures five different types of particular product (consumer durable) coded A, B, C, D and
E. The weekly market demands and selling prices were also shown all top of Figure1. All the calculations
were done on Indian currency (Rs). Raw material passes through differ internal resources as shown in
Figure 1, Raw materials to manufacture product A were A1, A2, A3, A4, A5, A6, A7, A8, A9, A10,
A11and A12 as shown in Figure1. Similarly for product B. raw materials were B I, B2, B3, B4, B5, BG,
B7, B8, B9, Bl0, B11 and B12, for C, raw materials were Cl, C2, C3, C4, C5, C6, C 7, C8, C8, C9, Cl0,
C11, and C12 and for D, raw materials were Dl, D2, D3, D4,.D5, D6, D7, D8, D9, D l0, D 11 and D12.
Again for E, raw materials were El, E2, E3, E4, E5, EG, E7, E8, E9, El0, Ell and E 12. Cost of various raw
materials for product A, B, C, D and E were given in (Table B). Material passes through total twelve types
of work centre(WC). Work centre for certain operation were double for Example, WC1 to meet the
demand. In case of final assembly there were three work centre (WC 8). Dark lines indicates flow path
shown in Figure1 of particular component route that component passes through work centre 10, 6 and
assembled at work centre 8. Another component passes through Work Centre1,2,3,4,5,6,7, and assembled
at Work Centre 8. Third one passes through work centre 9, 12 and assembled at Work Centre 8. To
manufacture these products, materials passes through various work centre. Times consumed by these
materials at various work centre are given at (Cycle time and capacity utilisation) (Table A). Column two
represents the processing time of components at various Work Centre to manufacture A, to manufacture A
raw material A1 at WC1 required 0.23 min. Then A1 and A2 combined at WC2 required 0.25 min
likewise column 3 ,4 ,5,6, represents time taken by various work centre to process B,C,D,E.
Company runs for six days in a week with single shift. Overhead expenses per week for organization were
Rs 4104000. Set up time for all the stations on an average taken was 12 min /setup. On any particular day
maximum no. of set up required was one. Set up time and no of set ups per day was assumed so after
analysis of last six months data. Weekly capacity for work center (WC) was calculated as follows, there
were two number of WC1. For daily 8 hrs run total weekly time was(48ร 6) = 5760 min. calculation of
2ร
weekly setting time was 12 min per set up, one WC required one set up, a two nos of WC1 that is
12ร 6=144 min .Weekly capacity (total weekly time- time lost due to sets up) is equal to 55760-
2ร
144=5616 min.
From (Table A), we clear that 9WC and 10 WC are constrained Resource. The WC5, 6, 7 utilized work
center least. To over come the problems, suggestions given to management was to run all three. Total
capacity increased was 180ร that is 540. Only one work centre 10 was run for five days, so capacity
3
increased in work center 10 was (30ร 5=150min). Overhead expenses remained the same.As seen in Table
A, for product cost calculation and raw material price to manufacture A (A1, A2,A3,A4, ..............A12) was
Rs.498.2 Product A consumes 2.77 min as seen in Table B. Cost of 2.77 min was (2.77ร 62.87) =Rs.174.15
Profit per working min for all the products was calculated. As per standard accounting higher
profit/working min was the indication of manufacturing priorities.
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6. Mathematical Theory and Modeling www.iiste.org
ISSN 2224-5804 (Paper) ISSN 2225-0522 (Online)
Vol.2, No.2, 2012
Thus sequences of priorities were A, B, E, C, and D. As seen in (Table C), one unit of A consumes 0.55
min of constrained resource. After producing all "A" (8200) still some constraint resource time available on
hand. Total product throughput calculation for B was = (9089 ร 275.2) + (1411 ร 80) which was equal to
Rs.2614173. Similarly throughput for other products was calculated. Net profit as per standard accounting
was Rs.1330433 which can be seen in (Table C). In TOC analysis (Table D) throughput/constraint
resource min was found out, which is different from standard accounting,. It considers all resources
equality. Throughput per manufactured unit of product A was equal to 800- 498.2=301.8 Throughput per
contracted unit of A was equal to 800-700 = 100. Total product Throughput calculation for A was equal to
6943 ร 301.8 + (1257ร 100) which was equal to Rs. 2221097. Similarly throughput for other products was
calculated.
Net Profit in that case increased from standard accounting system by Rs. (1352197-1330433) =
Rs.21764, that is increased by 1.63%
Products throughput and net profit was calculated as described in earlier two cases.
In LP analysis based on TOC model, net profit increased by (1399630-1330433) = Rs.62421 from
standard accounting, that is 5.2% and Rs. 47433 or 3.51% from TOC model.
This problem can be solved by the LP objective function also as follows
Zmax = (700-498.2) A + (680- 484.8) B+ (640 - 471.8) C + (640 - 462.2) D + (625 - 446.35) E,
Subject to the following constraints
Technological Constraints
0.23A+0.22B+0.2C+02D+0.21E < 5616
0.25A+0.23B+0.22C+0.22D+0.2E < 5616
โฆโฆ โฆโฆ. โฆโฆโฆ
0.1A+0.1B+0.1C+0.1D+0.1E<2808
Market constraints
A=8200, B=10500, C=1550, D=1350, E= 2400 and A, B, C, D, E = 0
The resulting optimum product mix is same as given in (Table E), that is to manufacture 2572, 10500,
1550, 1350, 2400 of A,B,C,D,E respectively.
8. Results
The details of comparisons of three models are given in (Table F). The LP model based on TOC suggested
manufacturing 2572 numbers A, 10500 of B, 1550, of C 1350, of D and 2400 of E and to outsource 5628 of
A only is shown in (Table F). Similarly to manufacture and to outsource quantity suggested by TOC and
SAC models can be depicted in Table F. After going through this an analysis by a cross-functional team,
management decided to implement this model under sudden increase in order.
9. Conclusions and Suggestions
For unbalanced manufacturing systems, TOC constitutes a useful strategy for maximising and improving
system performance. We have shown that the operational research technique of mathematical programming
provides a systematic basis for the implementation of TOC in practice. A substantial scope exists for
developing mathematical models of TOC in automated manufacturing systems and their validation in
industrial practice.
References:
Atwater J.B. and S. Chakravorty, (1995)โUsing the Theory of Constraints to guide implementation quality
Improvement Projects in Manufacturing Operationsโ, International Journal of Production Research, Vol
33, No 6, pp 1761 โ 1784.
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7. Mathematical Theory and Modeling www.iiste.org
ISSN 2224-5804 (Paper) ISSN 2225-0522 (Online)
Vol.2, No.2, 2012
Bhattacharya, A., and Vasant P., and Sarkar, B and Mukherjee, S.K., (2008)โA Fully Fuzzified, intelligent
theory-of-constraints product mix decisionโ, International Journal of Production Research, Vol. 46, No. 3,
789-815.
Chakraborty P.S, Majumder G. Sarkar B. (2006) โConstraint Recourse Management and Production
Related Decision- a Case Studyโ, Journal of Institute of Engineering Vol 86 March pp 48-53
Chiu M and Grier L (2008)โCollaborative supply chain planning using the artificial neural network
Approachโ Journal of Manufacturing Technology Management Vol 15 Number 8 pp 787-796
Draman R.H, Lockman A.I. and Cox F (2002) โConstrained based accounting and its impact on
organizational performance: a simulation of four common business strategiesโ. Journal of Integrated
manufacturing System 1314 pp 190-200.
Jain A.K, Elmaraghy H.A.(1997)โProduction Scheduling/rescheduling in flexible manufacturingโ.
International Journal of Production Research 35,281- 309
Qassim R.Y. (2000) โTheory of Constraints in Manufacturingโ, Journal of the Brazilian Society of
Mechanical Sciences Vol 22 No 4 Rio de Janerio, pp 82-88
Bharat Chede has received Bachelorโs degree from Amravati University, India and Masters Degree in
Mechanical Engineering (Production Engineering) from Shivaji University, India, He is currently pursuing
PhD from Rajiv Gandhi Proudyogiki Vishwavidyalaya Bhopal, India. He is working as Head of
Department (Mechanical Engineering) at Mahakal Institute of Technology and Management Ujjain India.
His Current area of research is Optimization in manufacturing techniques using fuzzy logics.
Dr C.K.Jain Phd in ProductionEngineering from IIT Rourkee. A renowned academician, was responsible
for making trendsetting transformations during his last stint as Principal, UEC. Having received a Gold
Medal in M.Tech and an award winning research scholar during his PhD. His Current area of research is
Casting methods optimization.
Dr S.K.Jain. Phd from APS university Rewa India. He is principal Ujjain Engineering College Ujjain,
India . His current areas of research are Fuzzy logic Technique in Engineering
Aparna Chede has received Bachelors and Masters Degree in Mechanical Engineering from Rajiv Gandhi
Proudyogiki Vishwavidyalaya Bhopal, India. She is currently working as Lecturer in Mechanical
Engineering at Mahakal Institute of Technology and Science Ujjain India. Her current areas of research are
Industrial Engineering techniques.
30