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This book describes a vision of manufacturing in the twenty-first century that maximizes efficiencies and improvements by exploiting the full power of information and provides a research agenda for information technology and manufacturing that is necessary for success in achieving such a vision. Research on information technology to support product and process design, shop-floor operations, and flexible manufacturing is described. Roles for virtual manufacturing and the information infrastructure are also addressed. A final chapter is devoted to nontechnical research issues.
This paper treats a two-echelon inventory system. The higher echelon is a single location reffered to as the depot, which places orders for supply of a single com modity. The lower echelon consists of several points, called the retailers, which are supplied by shipments from the depot, and at which random demands for the item occur. Stocks are reviewed and decisions are made periodically. Orders and/or shipments may each require a fixed lead time before reaching their respective desti nations. Section II gives a short literature review of distribution research. Section III introduces the multi-echelon distribution system together with the underlying as sumptions and gives a description of how this problem can be viewed as a Markovian Decision Process. Section IV discusses the concept of cost modifications in a distribution context. Section V presents the test-examples together with their optimal solutions and also gives the characteristic properties of these optimal solutions. These properties then will be used in section VI to give adapted ver sions of various heuristics which were used in assembly experiments previously and which will be tested against the test-examples.
This book presents selected contributions on a wide range of scientific and technological areas covered by AITeM (the Italian Association of Manufacturing). It discusses the following topics: additive manufacturing, advanced and unconventional machining and processes, material removal processes, foundry and forming, tools and machine tools, assembly/disassembly, joining materials and material properties, quality metrology and material testing, manufacturing systems engineering, sustainable manufacturing, smart manufacturing and cyber-physical systems, education in manufacturing and human factors, industrial applications. Written by young AITeM associates, the contributions reflect the multifaceted nature of the research in manufacturing, which takes advantage of emergent technologies and establishes interdisciplinary connections with various scientific and technological areas to move beyond simple product fabrication and develop a complex and highly interconnected value creation processes ecosystem pursuing high-value-added products to compete globally.
This book proposes a concept of adaptive memory programming (AMP) for grouping a number of generic optimization techniques used in combinatorial problems. The same common features seen in the use of memory and a local search procedure drive these emerging optimization techniques, which include artificial neural networks, genetic algorithms, tabu search and ant systems. The primary motivation for AMP, therefore, is to group and unify all these techniques so as to enhance the computational capabilities that they offer for combinatorial problems encountered in real life in the area of production planning and control.The text describes the theoretical aspects of AMP together with relevant production planning and control applications. It covers the techniques, applications and algorithms. The book has been written in such a way that it can serve as an instructional text for students and those who are taking tuition on their own. The numerical examples given are first solved manually to enhance the reader's understanding of the material, and that is followed by a description of the algorithms and computer results. This way, the student can fully follow the material. The algorithms described for each application are useful to both students and practitioners in grasping how to implement similar applications in computer code using emerging optimization techniques.
At the crossroads of artificial intelligence, manufacturing engineering, operational research and industrial engineering and management, multi-agent based production planning and control is an intelligent and industrially crucial technology with increasing importance. This book provides a complete overview of multi-agent based methods for today’s competitive manufacturing environment, including the Job Shop Manufacturing and Re-entrant Manufacturing processes. In addition to the basic control and scheduling systems, the author also highlights advance research in numerical optimization methods and wireless sensor networks and their impact on intelligent production planning and control system operation. Enables students, researchers and engineers to understand the fundamentals and theories of multi-agent based production planning and control Written by an author with more than 20 years’ experience in studying and formulating a complete theoretical system in production planning technologies Fully illustrated throughout, the methods for production planning, scheduling and controlling are presented using experiments, numerical simulations and theoretical analysis Comprehensive and concise, Multi-Agent Based Production Planning and Control is aimed at the practicing engineer and graduate student in industrial engineering, operational research, and mechanical engineering. It is also a handy guide for advanced students in artificial intelligence and computer engineering.
At the crossroads of artificial intelligence, manufacturing engineering, operational research and industrial engineering and management, multi-agent based production planning and control is an intelligent and industrially crucial technology with increasing importance. This book provides a complete overview of multi-agent based methods for today’s competitive manufacturing environment, including the Job Shop Manufacturing and Re-entrant Manufacturing processes. In addition to the basic control and scheduling systems, the author also highlights advance research in numerical optimization methods and wireless sensor networks and their impact on intelligent production planning and control system operation. Enables students, researchers and engineers to understand the fundamentals and theories of multi-agent based production planning and control Written by an author with more than 20 years’ experience in studying and formulating a complete theoretical system in production planning technologies Fully illustrated throughout, the methods for production planning, scheduling and controlling are presented using experiments, numerical simulations and theoretical analysis Comprehensive and concise, Multi-Agent Based Production Planning and Control is aimed at the practicing engineer and graduate student in industrial engineering, operational research, and mechanical engineering. It is also a handy guide for advanced students in artificial intelligence and computer engineering.
Various Multiple Criteria Decision-Making (MCDM) techniques in one book: 13 MCDM techniques have been applied, namely, WSM, WPM, WASPAS, GRA, SMART, CRITIC, ENTROPY, EDAS, MOORA, AHP, TOPSIS, VIKOR, and new tools: MDEMATEL, Fuzzy MDEMATEL, Modified Fuzzy TOPSIS and Modified Fuzzy VIKOR. To date, no other book possesses this many tools. Various quantitative techniques: Different quantitative techniques have been applied, namely, Cronbach alpha, Chi-square and ANOVA (for demographic analysis), Percent Point Score and Central Tendency (response analysis), Factor Analysis, Correlation and Regression. To date, no other book possesses this many tools. Interpretive Structural Modelling: ISM has been applied for verifying MCDM results through MICMAC analysis and ISM model thus paving the way for model through SEM. Structural Equation Modelling: SEM using AMOS in PASW has been applied for model development. New MCDM techniques developed: In the process during qualitative analysis, new tools have been developed and their results have been compared with other existing MCDM tools and the results are encouraging. The new techniques are MDEMATEL, Fuzzy MDEMATEL, Modified Fuzzy TOPSIS and Modified Fuzzy VIKOR. Qualitative Model Developed: As the title says, Sustainable Green Development and Manufacturing Performance through Modern Production Techniques. It is a need-of-the-hour topic, as industries must maintain their performance (sustainable development) and, while sustaining, they have to keep in mind green issues (that is, environment-related issues, especially during the COVID-19 pandemic) and adopt advanced manufacturing and maintenance techniques. A model for this has been developed which will be helpful to both academicians and industrialists. Real-time Case Studies: Case studies in two industries of differing origins, different manufacturing sectors, different products, and comparing their units in the country of their origin and India. Dr. Chandan Deep Singh is an assistant professor in the Department of Mechanical Engineering, Punjabi University, Patiala, Punjab (India). He is a co-author of Adolescents, Family and Consumer Behaviour (Routledge, 2020) and of Manufacturing Competency and Strategic Success in the Automobile Industry (CRC Press, 2019). Dr. Harleen Kaur is a manager (HR) at DELBREC Industries, Pvt. Ltd., Chandigarh. She co-authored Adolescents, Family and Consumer Behaviour (Routledge, 2020).