Management of high-variety, complex production in job shops needs more than what is offered by well known manufacturing methodologies like lean manufacturing. This article proposes a complementary, scientific, quantitative, practical approach to manage such complex systems.
Production and operations managment notesWasim Arshad
This document provides an overview of production and operations management (POM). It discusses the key components of POM which include product, plant, processes, programmes, and people. It also covers different types of production methods such as job, batch, flow, and group. Additionally, it introduces concepts like capacity management, break-even analysis, and quality management. The document is an introductory chapter that lays the foundation for further concepts in POM.
The document describes the Transformation Process Model, which is used to understand how organizations work and guide redesign efforts. The model reduces complexity by focusing on eight key variables that must be aligned for success. It also defines transformation as any process that takes inputs, adds value through conversion, and provides outputs for customers. The rest of the document provides more details about the various components of the Transformation Process Model, including inputs, transformation/conversion processes, outputs, and control mechanisms.
This document provides a preface and table of contents for a book on production and operations management. The preface discusses revisions made for the second edition, including adding content on managing global operations, revising several chapters, and including caselets and skill development exercises. The table of contents provides an overview of the 10 chapters that make up the book, covering topics like plant location and layout, materials management, quality control, and work study.
This presentation discusses different process strategies including process-focused, repetitive-focused, and product-focused strategies. It provides examples of each strategy and compares their advantages and disadvantages. A process-focused strategy uses general purpose equipment for low volume, high variety products. Repetitive-focused strategies organize facilities by modules for high volume standardized products. Product-focused strategies use specialized equipment for high volume, low variety production. Mass customization blurs the distinctions by enabling high volume, high variety production. The presentation also discusses production technologies, process redesign, and environmentally friendly processes.
You can buy it here: http://imojo.in/8pg6s9
This document is a quick guide to fresh engineers, diploma holders and second generation businessmen in understanding the basics of Production / Shop floor management in a manufacturing unit. This document covers the roles and responsibilities, Process flow, Do's and Don'ts, Lean Manufacturing basics, MIS reports to be generated and the analysis to be done. This would serve as an Induction Kit for anyone who is joining as a Production Engineer / Production Supervisor in a typical Indian manufacturing company.
The document discusses process selection and facility layout. It explains that process selection refers to how production will be organized and has implications for capacity planning, layout, equipment, and work systems. The main types of process selection are job shop, batch, repetitive/assembly, and continuous production. Effective facility layout depends on the type of process selection and aims to minimize transportation costs and distances. Key considerations for layout include production workflows, distances, costs, budgets, and utilities.
Production and Operations Management
Product Vs Service
Concept of Production and OM
Functions /Scope of POM
Operation Strategy
Transformation Process
Product Design & Product Process
History of POM
Issues in POM
This document presents a lecture on production management. It defines production management as planning and controlling industrial processes to ensure smooth operations at required levels. It notes production management is used in both manufacturing and service industries. The lecture outlines the objectives to understand the production process and strategic decisions. It introduces the concepts of a production system and operations strategy. Finally, it lists the ten strategic operations management decisions that are addressed.
Production and operations managment notesWasim Arshad
This document provides an overview of production and operations management (POM). It discusses the key components of POM which include product, plant, processes, programmes, and people. It also covers different types of production methods such as job, batch, flow, and group. Additionally, it introduces concepts like capacity management, break-even analysis, and quality management. The document is an introductory chapter that lays the foundation for further concepts in POM.
The document describes the Transformation Process Model, which is used to understand how organizations work and guide redesign efforts. The model reduces complexity by focusing on eight key variables that must be aligned for success. It also defines transformation as any process that takes inputs, adds value through conversion, and provides outputs for customers. The rest of the document provides more details about the various components of the Transformation Process Model, including inputs, transformation/conversion processes, outputs, and control mechanisms.
This document provides a preface and table of contents for a book on production and operations management. The preface discusses revisions made for the second edition, including adding content on managing global operations, revising several chapters, and including caselets and skill development exercises. The table of contents provides an overview of the 10 chapters that make up the book, covering topics like plant location and layout, materials management, quality control, and work study.
This presentation discusses different process strategies including process-focused, repetitive-focused, and product-focused strategies. It provides examples of each strategy and compares their advantages and disadvantages. A process-focused strategy uses general purpose equipment for low volume, high variety products. Repetitive-focused strategies organize facilities by modules for high volume standardized products. Product-focused strategies use specialized equipment for high volume, low variety production. Mass customization blurs the distinctions by enabling high volume, high variety production. The presentation also discusses production technologies, process redesign, and environmentally friendly processes.
You can buy it here: http://imojo.in/8pg6s9
This document is a quick guide to fresh engineers, diploma holders and second generation businessmen in understanding the basics of Production / Shop floor management in a manufacturing unit. This document covers the roles and responsibilities, Process flow, Do's and Don'ts, Lean Manufacturing basics, MIS reports to be generated and the analysis to be done. This would serve as an Induction Kit for anyone who is joining as a Production Engineer / Production Supervisor in a typical Indian manufacturing company.
The document discusses process selection and facility layout. It explains that process selection refers to how production will be organized and has implications for capacity planning, layout, equipment, and work systems. The main types of process selection are job shop, batch, repetitive/assembly, and continuous production. Effective facility layout depends on the type of process selection and aims to minimize transportation costs and distances. Key considerations for layout include production workflows, distances, costs, budgets, and utilities.
Production and Operations Management
Product Vs Service
Concept of Production and OM
Functions /Scope of POM
Operation Strategy
Transformation Process
Product Design & Product Process
History of POM
Issues in POM
This document presents a lecture on production management. It defines production management as planning and controlling industrial processes to ensure smooth operations at required levels. It notes production management is used in both manufacturing and service industries. The lecture outlines the objectives to understand the production process and strategic decisions. It introduces the concepts of a production system and operations strategy. Finally, it lists the ten strategic operations management decisions that are addressed.
The document discusses operations management concepts related to just-in-time (JIT) and lean operations. It describes how Toyota Motor Corporation pioneered JIT and the Toyota Production System (TPS) to eliminate waste, reduce variability, and improve throughput. Key aspects of JIT/lean covered include minimizing inventory, reducing setup times and lot sizes, using level scheduling and kanban signals, and emphasizing continuous improvement.
This document provides an introduction to operations management. It discusses plant location factors and types of plant layouts, including product layout, process layout, and combination layout. It also covers network analysis tools like PERT and CPM. Additionally, it describes different types of production systems such as intermittent production (job production and batch production) and continuous production (mass production and process production). The key characteristics of each production system are defined.
The document provides an overview of production management concepts and issues faced by Pak Suzuki Motors Company Limited. It discusses key production management topics like the 7 Ms, plant layout, production planning, eliminating waste, and quality control. It also outlines real-life production issues at PSMCL like lack of coordination between planning and production control, issues with inventory management, and machines breaking down. The training aims to enhance production capabilities by linking conceptual knowledge to practical problems faced at the shop floor level.
This document provides an overview of Just-In-Time (JIT) manufacturing. It defines JIT as a method that organizes production so that parts are available when needed. The key aspects of JIT discussed include: eliminating waste through continuous improvement, leveling production using a pull system like Kanban, setting up cells/modules, reducing setup times, and ensuring quality from suppliers. JIT aims to provide customers what they want, when they want it, with no excess inventory or waste.
Just in time (JIT) is a production strategy that strives to improve a business' return on investment by reducing in-process inventory and associated carrying costs. Just in time is a type of operations management approach which originated in Japan in the 1950s. It was adopted by Toyota and other Japanese manufacturing firms, with excellent results: Toyota and other companies that adopted the approach ended up raising productivity (through the elimination of waste) significantly.
Operations management refers to administering business practices to maximize efficiency and profitability. It involves converting materials and labor into goods and services. The operations function creates and delivers products and services while evaluating quality, quantity, costs and fulfilling customer needs. Mass production and flexible production are two key production methods used. Production managers oversee resources to transform inputs into finished outputs through planning, implementing, and controlling production processes.
The document discusses operation management and production systems. It covers topics like production management, operations management, production system models, decisions made by operations managers, types of production systems, elements of operations strategy, operations competitive priorities, demand forecasting, and forecasting approaches. Specifically, it defines production management as applying management principles to converting raw materials into finished products. It also defines operations management as converting resources into more useful products or services.
The document provides an overview of operations management concepts including:
- The 10 decision areas of operations management including product/service design, quality, and capacity planning.
- Different types of production systems such as job shop, batch, and mass production and factors to consider when selecting a process.
- Key facility location factors and the general procedure for evaluating location alternatives.
Lecture notes of production & operation managementComplaint2015
Lectures notes
On
Production and Operation Management
Prepared by
Dr. Sarojrani Pattnaik
Dr. Swagatika Mishra
Assistant Professor
Department of Mechanical Engineering
VSSUT Burla
.
The Process Specialist mentors a team of 15-18 staff to provide accurate and timely financial data. They are responsible for ensuring the team's work is on time, accurate, and complete. The Process Specialist provides technical and content training to the team. They also identify process improvements, liaise with technology teams on developments, and collaborate with quality analysts. Administrative duties include performance management and other tasks assigned by management.
production and operations management(POM) Complete note kabul university
The Introduction to POM, Scope, Role, and Objectives of POM, Operations Mgt. – Concept; Functions
Product Design and its characteristics;
Product Development Process, Product Development Techniques.
This document discusses process selection and facility layout. It covers product design and how it defines key characteristics. It also discusses process selection as developing the necessary process to produce the designed product. Several factors that affect process design are discussed, including nature of demand, degree of vertical integration, production flexibility, automation, and quality. Different process flow structures like project, job shop, batch, assembly line and continuous are described. The product development process and tools to improve speed to market are outlined. Designing for factors like ease of production, quality and new services is covered. Finally, service process technology based on customer contact and labor/capital intensity is explained.
The document discusses various process strategies including process focus, repetitive focus, product focus, and mass customization. It describes the characteristics of each strategy and compares them in terms of factors like volume, variety, equipment used, and costs. The document also covers topics like process analysis and design tools, production technology alternatives, using technology in services, and process reengineering.
Process Characteristics in Operations: Volume, Variety, Flows, Types of Processes & Operations System, continuous flow & intermittent flow system. Process Product Matrix: Job production, batch production, Assembly line & Continuous flow process & production layout Service System Design Matrix: Design of Service system, Service Blue print
Production and operation management ppt @ bec doms bagalkot Babasab Patil
Production management involves understanding production systems and dynamics to achieve quality, productivity, delivery performance and customer satisfaction at low cost. Advanced methodologies like CAD, CIM, JIT and lean manufacturing help optimize production through integrated information systems. Operations management coordinates production activities like planning, scheduling and quality control to efficiently transform inputs into outputs. Strategic decisions consider strengths, weaknesses and the environment to formulate operations strategies to maximize competitiveness.
Pgbm03 MBA OPERATION MANAGEMENT session 01 introduction to operationsAquamarine Emerald
This document provides an introduction and overview of the PGBM03 Operations Management course. It discusses how the course is structured over 10 lectures and 9 seminar classes. Students will complete a 3,000 word management report assessing the operational methods of an organization. To do well, students must address all learning outcomes, critically assess strategies and processes, and make recommendations. The document then defines operations management as the activities that transform inputs like materials, information, and customers into outputs like products and services. It provides examples of operations in a bakery and HR department. Finally, it discusses the different levels of analysis in operations management and the responsibilities of operations managers in designing, delivering, directing operations to achieve strategic objectives and competitive position.
The document contrasts the conventional (mass production) and lean approaches used by Joe and Ralph for assembly design and production.
Joe uses a conventional push system with make-to-assembly, large batches, slow pace due to problems and errors, large inventory, wasted resources from errors and defects, necessary rework, low productivity from waiting times and inactive workers, an authoritarian leadership style, and poor worker motivation and individualistic behavior.
Ralph uses a lean pull system with make-to-order, small lots for constant adaptability, smooth pace with no waiting times or inactive operators, no inventory, no waste from an efficient assembly line, continual improvement to address potential errors, high productivity from collaboration and no wasted time
The document defines key terms related to process analysis such as process, cycle time, and utilization. It describes how process flowcharting can be used to diagram major process elements like tasks, decisions, and flows. Common flowchart symbols are defined. The document also discusses different types of processes like single-stage, multi-stage, make-to-order, and make-to-stock. Various process performance metrics are introduced like throughput time, velocity, cycle time, and utilization. Finally, the document covers different process types like continuous, batch, repetitive/assembly line, and job shop.
The document discusses different types of manufacturing and service processes. It identifies 5 main types of manufacturing processes: repetitive, discrete, job shop, continuous, and batch. It also discusses factors that affect process design decisions and types of service processes such as line operations, job shop operations, and intermittent operations. The degree of customer contact in a service process also impacts operations management.
The document discusses developing an operations strategy. It explains that operations strategy focuses on capabilities that give a competitive edge, called competitive priorities. Companies can excel at cost, quality, time/speed, or flexibility. It then provides details on each competitive priority, describing characteristics companies aim for when focusing on that priority. For example, when focusing on cost, companies aim to cut costs and eliminate waste. When focusing on quality, companies aim for high-performance design and consistency. The document also discusses types of manufacturing systems like intermittent, continuous, mass production and process production systems.
Lean production is an approach that focuses on eliminating waste to ensure quality. It involves implementing techniques like just-in-time production, cell production, and continuous improvement (Kaizen) to streamline processes. The goal is to cut costs by reducing overproduction, waiting times, transportation, excess stocks, unnecessary motion, and defects. Key aspects include time-based management to reduce wasted time, simultaneous engineering for faster product development, and cultivating a culture of participation and continuous improvement.
The document discusses operations management concepts related to just-in-time (JIT) and lean operations. It describes how Toyota Motor Corporation pioneered JIT and the Toyota Production System (TPS) to eliminate waste, reduce variability, and improve throughput. Key aspects of JIT/lean covered include minimizing inventory, reducing setup times and lot sizes, using level scheduling and kanban signals, and emphasizing continuous improvement.
This document provides an introduction to operations management. It discusses plant location factors and types of plant layouts, including product layout, process layout, and combination layout. It also covers network analysis tools like PERT and CPM. Additionally, it describes different types of production systems such as intermittent production (job production and batch production) and continuous production (mass production and process production). The key characteristics of each production system are defined.
The document provides an overview of production management concepts and issues faced by Pak Suzuki Motors Company Limited. It discusses key production management topics like the 7 Ms, plant layout, production planning, eliminating waste, and quality control. It also outlines real-life production issues at PSMCL like lack of coordination between planning and production control, issues with inventory management, and machines breaking down. The training aims to enhance production capabilities by linking conceptual knowledge to practical problems faced at the shop floor level.
This document provides an overview of Just-In-Time (JIT) manufacturing. It defines JIT as a method that organizes production so that parts are available when needed. The key aspects of JIT discussed include: eliminating waste through continuous improvement, leveling production using a pull system like Kanban, setting up cells/modules, reducing setup times, and ensuring quality from suppliers. JIT aims to provide customers what they want, when they want it, with no excess inventory or waste.
Just in time (JIT) is a production strategy that strives to improve a business' return on investment by reducing in-process inventory and associated carrying costs. Just in time is a type of operations management approach which originated in Japan in the 1950s. It was adopted by Toyota and other Japanese manufacturing firms, with excellent results: Toyota and other companies that adopted the approach ended up raising productivity (through the elimination of waste) significantly.
Operations management refers to administering business practices to maximize efficiency and profitability. It involves converting materials and labor into goods and services. The operations function creates and delivers products and services while evaluating quality, quantity, costs and fulfilling customer needs. Mass production and flexible production are two key production methods used. Production managers oversee resources to transform inputs into finished outputs through planning, implementing, and controlling production processes.
The document discusses operation management and production systems. It covers topics like production management, operations management, production system models, decisions made by operations managers, types of production systems, elements of operations strategy, operations competitive priorities, demand forecasting, and forecasting approaches. Specifically, it defines production management as applying management principles to converting raw materials into finished products. It also defines operations management as converting resources into more useful products or services.
The document provides an overview of operations management concepts including:
- The 10 decision areas of operations management including product/service design, quality, and capacity planning.
- Different types of production systems such as job shop, batch, and mass production and factors to consider when selecting a process.
- Key facility location factors and the general procedure for evaluating location alternatives.
Lecture notes of production & operation managementComplaint2015
Lectures notes
On
Production and Operation Management
Prepared by
Dr. Sarojrani Pattnaik
Dr. Swagatika Mishra
Assistant Professor
Department of Mechanical Engineering
VSSUT Burla
.
The Process Specialist mentors a team of 15-18 staff to provide accurate and timely financial data. They are responsible for ensuring the team's work is on time, accurate, and complete. The Process Specialist provides technical and content training to the team. They also identify process improvements, liaise with technology teams on developments, and collaborate with quality analysts. Administrative duties include performance management and other tasks assigned by management.
production and operations management(POM) Complete note kabul university
The Introduction to POM, Scope, Role, and Objectives of POM, Operations Mgt. – Concept; Functions
Product Design and its characteristics;
Product Development Process, Product Development Techniques.
This document discusses process selection and facility layout. It covers product design and how it defines key characteristics. It also discusses process selection as developing the necessary process to produce the designed product. Several factors that affect process design are discussed, including nature of demand, degree of vertical integration, production flexibility, automation, and quality. Different process flow structures like project, job shop, batch, assembly line and continuous are described. The product development process and tools to improve speed to market are outlined. Designing for factors like ease of production, quality and new services is covered. Finally, service process technology based on customer contact and labor/capital intensity is explained.
The document discusses various process strategies including process focus, repetitive focus, product focus, and mass customization. It describes the characteristics of each strategy and compares them in terms of factors like volume, variety, equipment used, and costs. The document also covers topics like process analysis and design tools, production technology alternatives, using technology in services, and process reengineering.
Process Characteristics in Operations: Volume, Variety, Flows, Types of Processes & Operations System, continuous flow & intermittent flow system. Process Product Matrix: Job production, batch production, Assembly line & Continuous flow process & production layout Service System Design Matrix: Design of Service system, Service Blue print
Production and operation management ppt @ bec doms bagalkot Babasab Patil
Production management involves understanding production systems and dynamics to achieve quality, productivity, delivery performance and customer satisfaction at low cost. Advanced methodologies like CAD, CIM, JIT and lean manufacturing help optimize production through integrated information systems. Operations management coordinates production activities like planning, scheduling and quality control to efficiently transform inputs into outputs. Strategic decisions consider strengths, weaknesses and the environment to formulate operations strategies to maximize competitiveness.
Pgbm03 MBA OPERATION MANAGEMENT session 01 introduction to operationsAquamarine Emerald
This document provides an introduction and overview of the PGBM03 Operations Management course. It discusses how the course is structured over 10 lectures and 9 seminar classes. Students will complete a 3,000 word management report assessing the operational methods of an organization. To do well, students must address all learning outcomes, critically assess strategies and processes, and make recommendations. The document then defines operations management as the activities that transform inputs like materials, information, and customers into outputs like products and services. It provides examples of operations in a bakery and HR department. Finally, it discusses the different levels of analysis in operations management and the responsibilities of operations managers in designing, delivering, directing operations to achieve strategic objectives and competitive position.
The document contrasts the conventional (mass production) and lean approaches used by Joe and Ralph for assembly design and production.
Joe uses a conventional push system with make-to-assembly, large batches, slow pace due to problems and errors, large inventory, wasted resources from errors and defects, necessary rework, low productivity from waiting times and inactive workers, an authoritarian leadership style, and poor worker motivation and individualistic behavior.
Ralph uses a lean pull system with make-to-order, small lots for constant adaptability, smooth pace with no waiting times or inactive operators, no inventory, no waste from an efficient assembly line, continual improvement to address potential errors, high productivity from collaboration and no wasted time
The document defines key terms related to process analysis such as process, cycle time, and utilization. It describes how process flowcharting can be used to diagram major process elements like tasks, decisions, and flows. Common flowchart symbols are defined. The document also discusses different types of processes like single-stage, multi-stage, make-to-order, and make-to-stock. Various process performance metrics are introduced like throughput time, velocity, cycle time, and utilization. Finally, the document covers different process types like continuous, batch, repetitive/assembly line, and job shop.
The document discusses different types of manufacturing and service processes. It identifies 5 main types of manufacturing processes: repetitive, discrete, job shop, continuous, and batch. It also discusses factors that affect process design decisions and types of service processes such as line operations, job shop operations, and intermittent operations. The degree of customer contact in a service process also impacts operations management.
The document discusses developing an operations strategy. It explains that operations strategy focuses on capabilities that give a competitive edge, called competitive priorities. Companies can excel at cost, quality, time/speed, or flexibility. It then provides details on each competitive priority, describing characteristics companies aim for when focusing on that priority. For example, when focusing on cost, companies aim to cut costs and eliminate waste. When focusing on quality, companies aim for high-performance design and consistency. The document also discusses types of manufacturing systems like intermittent, continuous, mass production and process production systems.
Lean production is an approach that focuses on eliminating waste to ensure quality. It involves implementing techniques like just-in-time production, cell production, and continuous improvement (Kaizen) to streamline processes. The goal is to cut costs by reducing overproduction, waiting times, transportation, excess stocks, unnecessary motion, and defects. Key aspects include time-based management to reduce wasted time, simultaneous engineering for faster product development, and cultivating a culture of participation and continuous improvement.
Lecture 25 conversion cycle -wolrd class companies & lean manufacturing-...Habib Ullah Qamar
World class companies and lean manufacturing, What is world class company and it characteristics. How lean Manufacturing and its principles with tools and techniques automate production process. CAD, CAM, and CNC .
Operations - Introduction & Production SystemsRobbieA
Operations involves converting inputs like raw materials into outputs like finished goods through various processes. It is a core business function and important because it produces the products and services that generate profits. When deciding on a production system, key factors to consider include the nature of the product, required quantity, available resources, and business development stage. Production levels may vary due to changes in demand, staffing issues, equipment breakdowns, and maintenance needs.
Operations - Introduction & Production SystemsRobbieA
Operations involves converting inputs like raw materials into outputs like finished goods through various processes. It is a core business function and important because it produces the products and services that generate profits. When deciding on a production system, key factors to consider include the nature of the product, required quantity, available resources, and business development stage. Production levels may vary due to changes in demand, staffing issues, equipment breakdowns, and maintenance needs.
Chapter 5. Supply Planning: Meeting Customer Demand
After we’ve made our best estimate of a demand forecast for goods or services and netted it against our current and targeted inventory position to determine our future inventory requirements, it becomes necessary to make sure that we have enough capacity to meet the anticipated demand.
When we think of planning the capacity for a goods or service business, we typically think in terms of three time horizons:
Long range (1-3+ years) – Where we need to add facilities and equipment that have a long lead time.
Medium range (roughly 2 to 12 months), we can add equipment, personnel, and shifts; we can subcontract production and/or we can build or use inventory. This is known as “aggregate planning”.
Short range (up to 2-3 months) –Mainly focused upon scheduling production and people, as well as allocating machinery, generally referred to as production planning. It is hard to adjust capacity in the short run since we are usually constrained by existing capacity.
The supply chain and logistics function must actively support all of the above by supplying material and components for production and product to the customer and in fact has many of its own capacity constraints in terms of its distribution and transportation services.
In many service organizations, the actual work of capacity and supply planning for the production of inventory may be partially or totally in another organization as is the case of retailers or wholesalers. But even in those instances, retail and wholesale supply chain organizations are intertwined with the vendor’s manufacturing process, so they should participate, support and integrate vendor production plans into their own processes when possible. Additionally, service organizations have capacity constraints in terms of various resources that are impacted by inventory levels (ex: labor, warehouse capacity, back room retail storage, shelf space, etc). So it is well worth understanding the aggregate planning process no matter where you are in the supply chain.
The Process Decision
Stepping back for the moment, it should be understood that all organizations, both goods and services, have to make what is known as the process decision. That is, how the goods or services are to be delivered.
In most established organizations, there is already an existing process that is usually based upon the industry and managements competitive strategy.
Goods and Service Processes
Process choices in goods and service industries can be defined and delineated by what has become to be known as the “product-process matrix” (
Hayes and Wheelwright; 1979; Chart 5.1). In this model, an organization’s process choices are based upon both the volume produced and variety of products. At the upper left of the chart, companies are considered process oriented or focused and those in the lower right are considered product focused. The ultimate decision of where a firm lo.
Capacity planning involves both long-term and short-term considerations. Long-term capacity planning relates to strategic issues like facility locations and technology. Short-term capacity planning concerns scheduling, labor shifts, and balancing resource capacities to efficiently handle unexpected demand changes. Critical capacity decisions involve determining optimal levels of raw materials, equipment, labor, storage and integrating these factors based on demand forecasts. Capacity is impacted by various interrelated factors and effective planning is needed to meet requirements at minimal cost while maintaining quality and competitiveness.
This document discusses how tracking production downtime can help improve continuous improvement initiatives. It provides examples of using work sampling studies to identify sources of downtime at two manufacturing plants. This revealed significant unrecognized downtime and opportunities to increase uptime and capacity. Tracking downtime periodically provides visibility into improvement areas and can help focus continuous improvement efforts on issues with the biggest financial impact.
This document discusses different types of process flows and classifications for production processes. It describes three main types of process flows: line flow, intermittent/batch flow, and project flow. Line flow involves a linear sequence of standardized operations, like an assembly line. Intermittent flow involves production in batches using flexible, general-purpose equipment. Project flow is for unique, one-off products like works of art. The document also discusses how process selection decisions impact costs, quality, flexibility and other operational factors.
Lean production is an approach that focuses on eliminating waste to ensure quality. It involves doing simple things well, continuous improvement, and involving employees. The goal is to cut costs by reducing various types of waste like overproduction, waiting times, unnecessary transport and motion. Key aspects of lean production include just-in-time delivery from suppliers, cell production, simultaneous engineering, time-based management and continuous improvement through kaizen. Effective lean production requires good supplier relations, skilled employees and a culture of quality and change.
The document discusses capacity planning and management. It defines key terms like capacity, bottlenecks, utilization, and throughput. It outlines factors that determine effective capacity like facilities, processes, supply chain management and more. It discusses Eliyahu Goldratt's Theory of Constraints and how to identify, utilize, and elevate the constraint to improve the system. Common capacity planning strategies like leading, following and tracking capacity are also summarized. The document is intended to help participants plan capacity in their own areas and plants.
Lecture_3 (1).pptx facility layout and capacitypoonam1812yadav
This document discusses facility layout and capacity planning. It defines capacity planning and describes different time horizons for capacity planning, including long term, intermediate term, and short term. It also discusses different capacity planning strategies such as capacity lead, average capacity, and capacity lag strategies. The document then covers topics such as best operating levels, economies of scale, types of facility layouts including process and product layouts, and compares the characteristics of process and product layouts.
Operation engine ii session iv operations schedulingFatima Aliza
1) The document discusses various production planning and scheduling techniques used in job shop and process-focused manufacturing environments.
2) Key topics covered include master production scheduling, capacity requirements planning, input-output control, sequencing rules to determine job order, controlling changeover costs, and techniques for batch scheduling and delivery schedules.
3) The document provides details on several scheduling and sequencing methods including finite loading, earliest due date, economic order quantity, and line of balance.
Scheduling involves arranging workloads and allocating resources like machinery, employees, and materials. There are two main types of scheduling: operations scheduling, which assigns jobs and employees to time periods, and flow-shop scheduling for high-volume systems, where identical products flow through standardized processes. For low-volume job shops, scheduling is more complex due to custom orders and uncertain job requirements. Key considerations for both include sequencing jobs effectively and balancing workloads across workstations.
Similar to Scientific Management of High-Variety, Complex Production in Job Shops (20)
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on automated letter generation for Bonterra Impact Management using Google Workspace or Microsoft 365.
Interested in deploying letter generation automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Trusted Execution Environment for Decentralized Process MiningLucaBarbaro3
Presentation of the paper "Trusted Execution Environment for Decentralized Process Mining" given during the CAiSE 2024 Conference in Cyprus on June 7, 2024.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
Crucial components like the kernel and shell are dissected, highlighting their indispensable functions in resource management and user interface interaction. Das elucidates how the kernel acts as the central nervous system, orchestrating process scheduling, memory allocation, and device management. Meanwhile, the shell serves as the gateway for user commands, bridging the gap between human input and machine execution. 💻
The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
Moving to the realm of mobile devices, Das unravels the dominance of Android and iOS. Android's open-source ethos fosters a vibrant ecosystem of customization and innovation, while iOS boasts a seamless user experience and robust security infrastructure. Meanwhile, discontinued platforms like Symbian and Palm OS evoke nostalgia for their pioneering roles in the smartphone revolution.
The journey concludes with a reflection on the ever-evolving landscape of OS, underscored by the emergence of real-time operating systems (RTOS) and the persistent quest for innovation and efficiency. As technology continues to shape our world, understanding the foundations and evolution of operating systems remains paramount. Join Pravash Chandra Das on this illuminating journey through the heart of computing. 🌟
Operating System Used by Users in day-to-day life.pptx
Scientific Management of High-Variety, Complex Production in Job Shops
1. Scientific Management of High-Variety, Complex
Production in Job Shops
By
Prasad Velaga, PhD
Optisol ( http://www.optisol.biz )
College Station, Texas, USA
Email: prasad@optisol.biz
LinkedIn Profile: https://www.linkedin.com/in/prasadvelaga
Abstract
Many small and mid-sized job shops regularly face a lot of difficulty in managing their high-variety, complex
production for various reasons. In spite of worldwide promotion of several manufacturing methodologies like
lean manufacturing, a vast majority of job shops still do not seem to be confident that those methodologies
can adequately support efficient management of high-variety, complex production without demanding a lot of
system simplification. This article suggests a complementary, scientific, quantitative approach to fill in the
gap for efficient management of complex job shop production.
Introduction
It is not easy to find a universally accepted definition of job shop. However, many existing
definitions of job shop cover some important characteristics of job shops. Most manufacturing
units described as job shops are relatively small in size and revenue and accept a variety of
custom orders for small quantities. A job shop is more general than a production line that can
make a variety of products one after another sequentially. Job shops can be found among
industries described as:
Custom manufacturing units
Make-to-order (MTO) production units
Engineer-to-order (ETO) production units
High-variety production units
High-mix, low-volume production units
Order-driven production units
Specifically, job shops include many types of units like machine shops, fabrication shops, forge
shops, mold shops, tool & die shops, custom wood working units, furniture makers, repair shops,
laboratories, certain service units, etc. Management of multiple, concurrent projects which share
many common resources of limited capacity is often quite similar to production management in
job shops like fabrication units. The volume of custom production has been increasing over years
along with the level of automation in industries. Since mass production is getting outsourced, the
percentage of high-variety production units is increasing in western countries and the
2. methodology for improving the management of high-variety production in job shops is becoming
more relevant.
Many small and mid-sized job shops mostly deal with a variety of numerous, low-quantity orders
without any predictability of the process requirements and arrival times of orders. This
phenomenon involving unpredictable demand and unpredictable changes in product mix on shop
floor usually forces job shops to make products only against orders actually placed by customers.
The variation in product mix can make rapid fluctuations in the requirements of materials and
resources and small shops cannot afford to maintain inventories of a variety of raw materials for
supporting make-to-order production. For various reasons, job shops tend to use multi-functional
machines and multi-skilled workers of limited capacity to process customer orders.
Even if job shops can perform each production operation perfectly, eliminate defects and non-
value material handling and minimize all setup operations, all other factors mentioned above can
still make production management a true challenge for many job shops. In spite of this major
challenge, there is not much focus on the development of better solutions for management of
high-variety production probably because job shops which are small in size and revenue did not
attract the attention of management gurus. Many manufacturing experts suggest system
simplification to eliminate the complexity of high-variety production. System simplification is
not however always simple, easy or economical in practice, particularly for small job shops.
Without system simplification, management of high-variety, complex production is quite
difficult. System simplification suggested by lean manufacturing and the theory of constraints
(TOC) is still not widely implemented in high-variety, complex production systems. Even other
methodologies like Quick Response Manufacturing, Factory Physics, Mixed-Model Value
Streams, etc. are not still widely accepted by job shops for efficient production management. All
these methodologies seem to lack something that is essential to efficient production management
in many small and mid-sized job shops.
One of the objectives of job shops is to first maximize the overall shop performance by optimally
using the available resource capacities and then identify cost-effective simplifications as well as
opportunities for improvements that can yield the highest marginal gains in KPIs. A scientific
approach can help achieve this objective.
A Generic Description of Job Shops
A generic job shop with high-variety production is
fairly complex. It is not necessarily a production
line that makes a large variety of products
sequentially one after another. It is more complex
than a mixed model production system. Similarly,
it is more complex than a high-variety production
system consisting of one resource constraint and all
3. other resources with sufficient capacity. Some of the prominent features of job shops are:
A variety of small quantity orders (jobs) are received from customers with unpredictable
process requirements at unpredictable times
Jobs may have different quantities, material requirements, routings, priorities, target lead
times and margins
An order may involve producing a set of similar components or producing different types
of components and making subassemblies and a final assembly from thosecomponents
Several jobs may simultaneously move through the system along the respective routings
while competing for shared resources
Processing of a job may include some external operations
Production operations for a job may be sequential or they may have certain precedence
relations
The set of operations and precedence relations may vary with job
Setup times and cycle times of any operation may vary with job
Setup times for operations may also depend on job sequence
An operation may require a single resource or it may simultaneously require multiple
resources like machines, workers, etc.
Resources may be multi-functional machines and multi-skilled workers
Resources may have individual calendars (working hours) and calendar exceptions
A long operation may or may not be shared by several alternative resources for reducing
its duration.
Material of a job may move through the system as a single batch or as small transfer
batches.
Issues Faced by Job Shops
Job shop managers regularly face a lot of issues and challenges. The difficult issues faced by
many of them include:
Dealing with customer-imposed lead times and late changes in orders
Finding rational lead times for new jobs based on material lead times, the existing
workload and resource capacities
Finding right start times for jobs for controlling production lead times and WIP without
compromising the promised delivery dates
Estimating completion times of jobs
Foreseeing the imminent bottlenecks(due to changes in product mix) and mitigating them
in advance
Revising production plan subject to material delays for some jobs
Revising production plan subject to changes in job priorities
4. Capacity planning for meeting due dates of jobs which are likely to become late
Handling rush orders (hot jobs) for high margins with minimal effect on lead times of the
existing jobs
Estimating overtime requirements to handle rush orders without any adverse impact on
other orders
Overcoming interruptions caused by machine breakdowns and worker absence to avoid
late deliveries
Overcoming the adverse impact of rework / rejections
Managing overtime optimally to improve on-time delivery or accept rush orders.
Many of the above issues and challenges are absent or less severe in repetitive production
systems. They distinguish high-variety production of job shops from repetitive production.
Management of Job Shop Complexity
Some people in job shops are not confident of controlling and managing their production
efficiently in a proactive manner because they feel that their production system is subjected to
too many variables which cannot be duly taken into account. Many of these variables come from
the large known variation in the requirements of jobs for materials, processes and resources,
changes in job priorities, interruptions due to machine breakdowns, worker absence, uneven
availability of skills and machines over shifts, material delays, rework / rejection, etc. It is not
easy to take into account all such variables for managing complex, high-variety production.
Moreover, many job shops have to make a product mostly in response to an order received from
a customer. Job shops regularly face difficulty with production management mainly because of:
1. High variation in quantities and process requirements of orders
2. Unpredictable requirements of future orders for materials, processes and resources
3. Unpredictable ordering times
4. Frequent changes in job priorities or due dates
5. Continuously varying product mix
6. Simultaneous processing of multiple, diverse jobs using shared resources
7. Finite capacity of resources.
System Simplification
A rational approach to reducing the difficulty of managing job shop production is to simplify the
system sufficiently. It is better to pursue simplification as much as possible although there may
be some practical limits to it. Simplification may not always come for free. The following are
two practical methods for simplifying job shop production system:
I. Process flow analysis, part family identification, design of cells for
different part families and cellular manufacturing
5. II. Increase resource capacities sufficiently.
The first method can certainly reduce the above described complexity if resources can be
dedicated to various cells as required. It can be quite useful to parts manufacturing units.
However, in project-oriented job shop production like fabrication, this method may have certain
limitation. Job shop production management can be greatly simplified if resource capacities can
be increased as required. The simplification by capacity enhancement is not economically viable
for some small job shops because maintaining a lot of unused resource capacity can increase the
overall production cost. Some of the existing approaches to simplification are not effective in
this regard. For example,
a) Lean manufacturing approach involving takt time, line balancing, heijunka, VSM for
each product and good practices is not adequate for simultaneous processing of multiple,
diverse jobs
b) Capacity planning suggested by the theory of constraints (TOC) in the form of a single
constraint with full subordination for the purpose of system simplification is not accepted
by a vast majority of job shops probably because those shops do not find it cost effective.
Although simplification of complex, high-variety production is very desirable, it should not
compromise production flexibility of the shop.
A Comprehensive, Scientific, Model-Based Approach
For high-variety, complex production systems with moving bottlenecks, if simplification cannot
be achieved adequately in economic and affordable fashion, it is possible to make further
progress in production management by adopting a comprehensive (plant-level), scientific,
model-based, approach. This approach will duly take into account many variables which industry
people cannot consider in their decision making in a different approach. It involves:
1. Synchronization of production operations of jobs (subject to all relevant constraints)
2. Quick resynchronization in response to significant changes in the system
3. Reliable prediction of work progress, job completion times and bottleneck
formations over time
4. What-if analysis
5. Proactive capacity planning.
Operations synchronization provides an excellent guideline for organizing workload over time in
a systematic manner. It makes production management easier. Synchronization also provides
optimal job start times to minimize WIP and production lead times of jobs.
We can achieve the best synchronization by having a lot of resources but this option is not cost
effective. If resources are not always available as much as needed for processing multiple,
6. concurrent jobs of different routings, the best synchronization cannot be achieved by making
decisions based on only the existing situation at any time point. Whenever job shop managers
make decisions related to the flow (progress) of work, it is mostly done on the basis of the
existing situation. They use their experience, knowledge, commonsense and intuition in decision
making but not the prediction of how the work is going to progress and how the bottlenecks are
going to form over time. In other words, they do real-time decision making in the best possible
way. The real-time control systems do not take into account the future consequences of current
decisions and therefore, they cannot offer the best synchronization.
Kanban, the real-time control mechanism in reactive mode is not proven to provide the best
synchronization in high-variety, complex production. CONWIP, another method for production
control is not rigorous enough to deal with simultaneous processing of multiple jobs with
different routings and quantities. There is no convincing proof that even POLCA, a real-time
production control method of quick response manufacturing (QRM) offers the best
synchronization. In TOC, scheduling on the single constraint, timely release of material for jobs
and buffer management are supposed to offer good synchronization but ensuring a single
constraint with the necessary subordination appears to be a major economic challenge in many
small job shops.
Prediction of work progress, job completion times and bottleneck formations reduces
apprehension about how jobs will progress on shop floor, whether jobs can meet their due dates
and when and how bottlenecks are going to form. The predictive capability supports proactive
decision making. For high-variety complex production, proactive management based on both
real-time situation and workflow prediction is more effective than management based on only
real-time situation.
The predictive capability facilitates what-if analysis of workflow with respect to any
contemplated changes in a high-variety production system. What-if analysis helps managers to
evaluate and compare the effectiveness of various possible decisions on production and select the
best decision. Without prediction and what-if analysis functionality, people in complex
production make decisions based on real-time situation, experience, knowledge, commonsense,
guess work and hope. Such decisions may turn out to be quite disadvantageous sometimes.
Capacity planning is essential for managing high-variety, complex production systems in which
demand for resources keeps varying over time due to the changing product mix. It is needed for
many objectives like (a) accommodating rush orders, (b) implementing changes in order
priorities, (c) advancing due dates of some orders, (d) mitigating the moving bottlenecks, (e)
reducing the lead times of jobs that are likely to be late, etc. Capacity planning is relevant to any
system in which resources may not always have as much capacity as needed.
7. The above functionality can be achieved by using an appropriate, scientific model and right data
for a target production system. This approach complements 5S, good work culture, visual
management, improvements in setup time, cycle time and quality of individual operations and
improvements in material movement times on shop floor. It takes into account the stationary and
moving bottlenecks in the system.
Operations-Level Production Scheduling in Support of Scientific, Model-Based
Approach
The above described scientific approach to management of high variety, complex production can
be easily adopted with the help of a rigorous, scientific method for detailed (operations level)
production scheduling. To achieve the best operations synchronization in such systems, we can
optimally schedule in advance all production operations subject to all relevant constraints and
then implement the schedule with necessary perturbations in real time. An optimal production
schedule that satisfies all constraints provides the required synchronization.
A detailed production schedule specifies, for each operation of each job, a time interval with
feasible resource assignment. But, due to some uncontrollable natural variation in the system, we
will not be able to perform each operation exactly during its scheduled time slot. In the presence
of uncontrollable natural variation, the actual progress on shop floor increasingly deviates from
the detailed production schedule as time progresses, making the implementation of a detailed
schedule difficult. To overcome this difficulty, the detailed schedule can be converted into daily
dispatch lists (operation sequences) for resources.
It is much easier to implement, as a substitute for the detailed schedule, the resource dispatch
lists which are less sensitive to uncontrollable variation on shop floor. Implementation of
dispatch lists does not need the scheduled start and finish times of operations. Minor exceptions
to a dispatch list can be made in real time whenever necessary. The cumulative deviation of work
progress on shop floor from the schedule may keep increasing and make even dispatch lists
infeasible at some time point. Therefore, the schedule must be periodically revised along with
dispatch lists on the basis of the existing workload for controlling the deviation between the
actual work progress and the schedule. In the presence of uncontrollable natural variation, an
operations level production schedule (generated by even a powerful algorithm) serves as a
budget of resource available times for managing production over time. A good production
schedule can offer an excellent guideline for managing complex high-variety production.
A feasible, detailed production schedule provides a prediction of work flow, job completion
times and bottleneck formations over time. Inserting time buffers for jobs at bottlenecks in a
judicious manner (conceptually somewhat similar to drum-buffer-rope method of TOC) without
any adverse effect on shop performance, we can create a production schedule which determines
job completion times that are dependable even in the presence of uncontrollable natural
8. variation. One can perform fast and extensive what-if analysis of schedules when the scheduling
method is implemented by a software tool on computer. Any scheduling mechanism that
provides workflow prediction and facilitates extensive what-if analysis also supports capacity
planning.
It is also possible adopt the above described scientific approach to job shop management with the
help of discrete even simulation. But, for factory people without simulation experience, it is
much easier to run scheduling software as part of the approach.
Scheduling Solutions for High-Variety, Complex Production
Job shops currently use many methods for scheduling their high-variety production. The methods
include whiteboards, MRP scheduling, Excel applications, project management software like MS
Project, Drum-Buffer-Rope method of TOC and finite capacity scheduling (FCS) software. An
advanced planning and scheduling (APS) software is also an FCS tool that takes into account all
resource constraints. In this article, FCS refers to both FCS and APS. There are some drawbacks
with the above scheduling methods except FCS software to support the scientific, model-based
approach that is described earlier.
Whiteboard scheduling is too simple to support synchronization and quick resynchronization.
MRP scheduling is not helpful to high-variety systems because it works with unrealistic, simple
production models based on the assumption of infinite capacity. Many job shops are unhappy
with the scheduling function of their MRP systems. Dissatisfaction with MRP scheduling led to
creation of in-house, commonsense-based Excel applications in many job shops. However, many
in-house Excel applications for scheduling high-variety production are not rigorous enough to
generate a rational operations-level schedule that satisfies all constraints including resource
capacities. Project management software is generally known to be weak for automatically
creating a schedule without resource overloading. The required manual resource leveling in that
software is laborious and time consuming in production environment. Those tools are not
developed for scheduling production operations. It is very uncommon for any of the above
methods except FCS software to automatically generate a rational, detailed production schedule
at plant level subject to all important constraints. This is because they are not usually based on
rigorous scheduling models and logic.
Most FCS tools are based on a rigorous, scientific scheduling paradigm and use powerful
algorithms to generate an optimal operations-level production schedule subject to all relevant
constraints. For efficiently managing high-variety, complex production, they offer workflow
prediction and the best operations synchronization and support what-if analysis and accurate
capacity planning. The best synchronization corresponds to optimal job start times. For example,
look at Figures 1 and 2 shown below. Figure 1 displays a schedule (over several weeks) of about
9. 1900 operations of 114 jobs in a job shop. Each thin horizontal line in the chart represents the
schedule of one of 114 jobs. The green segment in the line represents the time during which at
least one operation is scheduled for the job and yellow segment mostly represents waiting time
of the job for an operation that needs a bottleneck resource. In this schedule, all operations of
every job are scheduled as early as possible subject to resource availability and operation
precedence relations without much synchronization.
Figure 2 displays a schedule of the same workload that provides operation synchronization while
inserting some waiting time for jobs before bottlenecks in order to absorb uncontrollable natural
variation. The lower envelope in Figure 2 gives optimal job start times. They are optimal in the
sense that an earlier start of a job may increase job lead time without advancing the job
completion time and a late start may delay the completion of the job and some of the subsequent
jobs.
Other methods of production management cannot determine such optimal job start times in
complex, high-variety production without system simplification.
Basic Functionality of FCS Tools
Although FCS tools have been available for production scheduling for at least 4 decades, they
were not well adopted by job shops in the past due to several reasons. Powerful and sophisticated
versions of FCS tools based on scientific scheduling methods are currently available. They take
into account what job shop people consider as numerous variables which contribute to the
difficulty of production management. These tools provide:
Prediction of workflow and bottleneck formations over time
Prediction of job completion times
Prediction of busy and idle times of resources over time
Estimates of percentage utilization of resources for any selected time interval
Graphic displays of job schedules and resource schedules
10. Support for fast and extensive what-if analysis
Support for proactive capacity planning.
This functionality provides excellent decision support for managing high-variety production. The
predictive capability of FCS tools enables managers to make better decisions in real time on the
basis of not only the existing situation but also the potential consequences of various possible
decisions. Such capability is unavailable in almost all other methods for high-variety production.
The ability to perform what-if analysis and proactive capacity planning quickly and accurately
gives a major advantage to managers of high-variety production. Short term operations-level
schedules provide good guidance for efficient control and management of high-variety
production as mentioned below.
Benefits of FCS Tools
FCS tools offer many short term benefits in support of efficient management of job shop
production. The benefits include the following:
A rational due date will be fixed for each new order by balancing customer aspiration and
the stress of production people in meeting the committed due date
An optimal start time will be determined for each new job for minimal production lead
time without any adverse effect on the job completion time (Earlier start may cause
longer lead time due to waiting in the priority line at bottlenecks while late start may
cause late completion time for the job)
The impact of accepting a rush order on completion times of the existing jobs can be
easily quantified (The quantification helps in making cost-benefit analysis of accepting
rush orders)
The impact of changing job priorities (or due dates) on job completion times can be
easily quantified
The existing workload can be rescheduled almost instantaneously in response to major
changes or interruptions in production due to factors like unexpected changes in job
priorities, machine breakdowns, worker absence, material delays, rework, etc.
Long-term production scheduling by FCS tools supports long-term capacity planning and
resource planning.
Why Did FCS Tools Fail To Receive Proper Recognition In Job Shops?
Many FCS tools developed decades ago are basically not suitable for detailed, operations-level
scheduling in job shops with high-variety, complex production. They used to take several hours
on main frame computers to generate a rational, resource-constrained schedule. Electronic shop
floor data collection systems were not available for updating job status information in support of
11. FCS implementation. Therefore, FCS software could not support quick schedule revisions and
what-if analysis. Poor utilization of FCS software was also caused by lack of training, improper
usage, cumbersome implementation (fixing several parameters of the software), user resistance,
lack of faith in the output, etc. Attempts to implement the exact scheduled start and finish times
of operations under the influence of uncontrollable variation can cause a lot of frustration with
FCS software.
Following the arrival of Microsoft Excel, planners and schedulers in job shops started developing
simple, in-house scheduling solutions for themselves using shop floor knowledge, experience
and commonsense. This development was driven, to a large extent, by the frustration with
scheduling modules of ERP / MRP systems for job shops. In many cases, job shop managers are
unhappy even with the performance of these simple, commonsense scheduling solutions in
Excel. Most in-house Excel applications for scheduling do not seem to be based on a rigorous,
scientific scheduling model. Those Excel applications are usually not rigorous enough to support
operations synchronization across the plant.
Some powerful versions of FCS tools started entering the market from mid 1990s. These tools
are scientific, rigorous, versatile and fast and also they have excellent, interactive graphic user
interface for displaying job schedules and resource schedules. Being fast, they support extensive
what-if analysis of schedules and proactive capacity planning in dynamic production
environment. Fortunately, these FCS tools found good support from the increasingly
sophisticated ERP systems and electronic shop floor data collection systems for getting the
required input data. However, even these modern FCS tools are not yet widely adopted across
the job shop world due to various issues including:
Price
Functionality
Suitability
User friendliness
Availability of up-to-date input data at the time of scheduling
Resistance to a new scheduling paradigm, a new way of schedule creation and a new
format of schedule
Manager’s desire to somehow make use of the weak scheduling module in the ERP /
MRP system
Scheduler's desire to continue with his /her current commonsense-based Excel
application for scheduling.
Every software described as a tool for finite capacity scheduling of production is not necessarily
efficient to support the scientific, model-based approach to production management described
earlier. An FCS tool must be really strong to schedule production operations optimally subject to
12. all constraints in order to support the approach. Right now, there are a limited number of FCS
tools in the market with such strength.
Summary
High-variety production is complex in many job shops due to several factors like unpredictable
process requirements of customer orders, need to make products only against received orders,
customer-imposed lead times, acceptance of rush orders, abrupt changes in order priorities,
machine breakdowns, worker absence, material delays, rework / rejections, continuous change in
product mix, simultaneous processing of several diverse jobs using many common resources of
limited capacity, etc. More importantly, job shops are usually on the receiving end of
negotiations with diverse customers.
Irrespective of the plant size and revenue level, many job shops find it difficult to control and
manage their high-variety, complex production. It is not always easy or economical to simplify a
job shop production system in order to make production management easy. Positive factors like
kanban-based production control, good practices, work culture, 5S, kaizen, etc. are not always
adequate to deal with production complexity in job shops. To handle some job shops efficiently,
we need more than 5S, takt times, Gemba walks, visual management and line balancing. Some
small and mid-sized job shops may real concerns to enhance resource capacities for achieving
subordination as part of TOC implementation. When production systems cannot be simplified as
desired, job shops need not be hopeless about efficient management of their complex, high-
variety production. With or without system simplification, job shops can still handle production
complexity efficiently by adopting the scientific, model-based approach described above. The
modern, powerful FCS software tools based on scientific scheduling models and rigorous logic
enable job shops to achieve it. People on shop floor need not develop scientific scheduling
models to adopt this approach. Versatile FCS tools come with a very generic scheduling
paradigm to cover a wide spectrum of job shops.
A powerful FCS software tool helps determine a rational due date and a right start time for each
new order based on the existing workload, resource requirements and resource capacities. It
precisely shows the effect of accepting a rush order or expediting an existing order on order
completion times. It also shows the effect of changing order priorities on order completion times.
It foresees changes in bottlenecks as product mix changes over time and enables capacity
planning by means of quick what-if analysis. This functionality itself will be of immense value to
complex job shops even if the software is not to be used for scheduling production operations on
a daily basis. FCS software can serve as a powerful decision support tool in managing complex,
high-variety production. Information systems currently being used by industries can greatly
support FCS implementation.