Handbook of Production Management Methods Episode 11 pot

290 Handbook of Production Management Methods 8. Niessink, F. and Van-Vliet, H., 1999: Measurements should generate value, rather than data [software metrics]. In Proceedings Sixth International Software Metrics Symposium (Cat. No.PR00403). IEEE Computer Society, Los Alamitos, CA, pp. 31–38. 9. Rigby, K.D., 1994: How to manage the management tools, Planning Review , 21 (6), 8–15. 10. Riggs, L.J. and Felix H. Glenn, 1983: Productivity by Objectives , Prentice-Hall. 11. Schneider, J.G., Boyan, J.A. and Moore, A.W., 1998: Value function based produc- tion scheduling. In Machine Learning. Proceedings of the Fifteenth International Conference (ICML’98) . Morgan Kaufmann, San Francisco, CA, pp. 522–530. Value engineering M – 2b; 3b; 5c; 8b; 14b; 16d; * 1.3c; 1.5c; 2.2b; 3.2c Value engineering is defined as an organized effort directed at analysing the function of system, equipment, facilities, services and suppliers for the pur- pose of achieving the essential functions at the lowest overall cost. Value engineering is the process of engineering as much value into a part or product as possible. One traditional way to achieve this goal is to monitor the product over the first year of production and make engineering changes as the oppor- tunity arises. Value engineering becomes a planning phase in which engineer- ing takes information from support functions, including those of the supplier and customer, and includes these suggestions and concerns in the design. One of the most popular tools of value engineering is the ‘value engineering workshop’. Such a workshop follows standard activities based on value engin- eering methodology. The main characteristic of the workshop are as below. 1. Teamwork . It has been proved that cost reduction and design improvements are best achieved by teamwork. A value engineering study is conducted by a team of people with skills tailored to the subject or product area. Teams should normally possess engineering, production, logistics and purchasing talents. The team should be of no more than 10 people. 2. Effort concentration . Each team meeting should be of several days dur- ation. It is recommended that meetings be held at a remote location in order to have the team participants free from ordinary tasks. 3. Methodology . Value engineering sessions are conducted in a manner that forces the team to work in a systematic and organized way. According to value engineering only such a methodology will achieve good results. The methodology is as follows: 1. Investigation phase . In this phase the team study the existing design or method. The team analyses and recognizes the functions of the product and 0750650885-ch005.fm Page 290 Friday, September 7, 2001 5:00 PM 110 manufacturing methods 291 defines the logistic connections and the importance of the different func- tions. In the next step the ‘worth’ of each function is evaluated. It is a sub- jective evaluation based on team intuition and experience. Comparing the different worths of the functions and the improvement costs indicates the priority of each function. 2. Speculation phase . This phase is aimed to generate ideas and alternatives. Techniques such as brainstorming and green light thinking are used. The main procedure is to separate idea generation from the evaluation of ideas. In addi- tion, a checklist might help to steer the thinking flow. 3. Evaluation phase . In this phase the alternatives are evaluated, and the real cost of implementing each alternative is established. In order to establish this cost, meetings are held with engineers, suppliers and any one else who can help evaluate the real cost. 4. Presentation phase . Even good ideas have to be ‘sold’. In this phase the team prepares a presentation for management. 5. Implementation phase . Value engineering results are judged by the results and not by the written proposal. Therefore the team must be part of the imple- mentation of the alternative selected. Bibliography 1. Billinton, R. and Wang, P., 1998: Distribution system reliability cost/worth analysis using analytical and sequential simulation techniques. IEEE Transactions on Power Systems , 13 (4), 1245–1250. 2. Farag, A.S., Shwehdi, M.H., Belhadj, C.A., Beshir, M.J. and Cheng, T.C., 1998: Application of new reliability assessment framework and value-based reliability planning. In Powercon ’98. 1998 International Conference on Power System Tech- nology . Proceedings (Cat. No.98EX151). IEEE, New York, 2 , 961–967. 3. Fong, S.W., 1998: Value engineering in Hong Kong – a powerful tool for a chan- ging society, Computers & Industrial Engineering , 35 (3–4), 627–630. 4. Jones, C., Medlen, N., Merlo, C., Robertson, M. and Shepherdson, J., 1999: The lean enterprise, BT Technology Journal , 17 (4), 15–22. 5. King, A.M. and Sivaloganathan, S.M., 1998: Development of a methodology for using function analysis in flexible design strategies. Proceedings of the Institution of Mechanical Engineers, Part B (Journal of Engineering Manufacture) , 212 (B3), 215–230. 6. Marples, A., 1999: Recycling value from electrical and electronic waste. Recycling Electrical and Electrical Equipment. In Conference Proceedings . ERA Technology Ltd, Leatherhead, pp. 4/1–7. 7. Momoh, J.A., Elfayoumy, M. and Mittelstadt, W., 1999: Value-based reliability for short term operational planning, IEEE Transactions on Power Systems , 14 (4), 1533–1542. 8. Niessink, F. and Van-Vliet, H., 1999: Measurements should generate value, rather than data [software metrics]. In Proceedings Sixth International Software Metrics Symposium (Cat. No.PR00403). IEEE Computer Society Los Alamitos, CA, pp. 31–38. 0750650885-ch005.fm Page 291 Friday, September 7, 2001 5:00 PM 292 Handbook of Production Management Methods 9. Schneider, J.G., Boyan, J.A. and Moore, A.W., 1998: Value function based produc- tion scheduling. In Machine Learning. Proceedings of the Fifteenth International Conference (ICML’98) . Morgan Kaufmann, San Francisco, CA, pp. 522–530. 10. Sik-Wah-Fong-P. and Dodo-Ka-Yan-Ip., 1999: Cost engineering: a separate academic discipline? European Journal of Engineering Education , 24 (1), 73–82. Virtual company S – 3b; 4c; 8c; 11b; 13d; 14c; * 1.1b; 1.2c; 2.2b; 3.3c; 3.6c; 4.2c See Virtual manufacturing. Virtual enterprises M – 2c; 3b; 4c; 7c; 8b; 9c; 10c; 11b; 13b; 16c; * 1.1b; 1.2c; 1.6c; 3.2c; 3.6c; 4.1b; 4.2c; 4.3c A virtual enterprise is composed of several companies, which are enabled to make joint commitments to their common customers. Although the companies are involved in a tight relationship in order to make joint commitments, they still retain their autonomy. Virtual enterprise is a technique that enables a large number of interested parties to use and enhance vast quantities of information that involves a number of information sources and component activities. Without principled tech- niques to coordinate the various activities, any implementation would yield disjointed and error-prone behaviour, while requiring excessive effort to build and maintain. Sometimes virtual enterprise might take the form of collaborative ventures with other companies, and sometimes it may take the form of a virtual company. The guiding principle of agile enterprise management is not automatic recourse to self-directed workteams, but for full utilization of corporate assets. The key to utilizing assets fully is the workforce. Flexible production technologies and flexible management enable the workforce of the agile manufacturing enter- prise to implement the innovations they generate. There can be no algorithm for the conduct of such an enterprise. The only possible long-term agenda is providing physical and organizational resources in support of the creativity and initiative of the workforce. Manufacturing is a standard application area for any approach that deals with information management in open environments. This is because modern manu- facturing is naturally distributed, involves a large number of autonomous commercial entities with a variety of heterogeneous information systems, makes use of human decision making, faces the realities of failure and exception in physical processes and contractual arrangements, and yet requires that the man- ufactured products meet design specifications and other quality requirements. 0750650885-ch005.fm Page 292 Friday, September 7, 2001 5:00 PM 110 manufacturing methods 293 Because they were not sensitive to these constraints, previous attempts at applying computing in manufacturing have had only limited success. With recent advances in the computing and communications infrastructure, there has been a recurrence of interest in manufacturing applications, especially in those dealing with the coordination of processes in different enterprises. Supply chains are the material flows that are arranged among different com- panies to accomplish a large manufacturing process. Traditional programming techniques are designed for closed environments, in which the programmer has (at least in principle) complete knowledge of the meaning of the information and full control over the disposition of the partici- pating activities. By contrast, in open environments, a programmer has partial knowledge of and virtually no control over the behaviour of the components created by other designers and being executed by autonomous users. Although preserving the autonomy of participating components is crucial, unrestrained autonomy would be risky, because it may easily lead to undesirable conse- quences. Nowhere are these concerns more urgent than in manufacturing. As manufacturing becomes increasingly reliant on the dynamic formation and management of extended and overlapping virtual enterprises, agent-based, flexible approaches will play an increasing role. Virtual enterprise seeks not data consistency directly, but a coherent state in the ongoing interactions of the participating components. This shift in focus from consistency to coherence not only facilitates automation, but is also more intuitive and closer to some aspects of human social behaviour. People cannot make irrevocable promises when they do not fully control their envir- onments, but they can warn each other of potential problems. For example, if an order is not going to come through, a good service would at least notify the others concerned. Bibliography 1. Davies, C.T., 1978: Data processing spheres of control, IBM Systems Journal , 17 (2), 179–198. 2. Dewey, A.M. and Bolton, R., 1999: Virtual enterprise and emissary computing technology, International Journal of Electronic Commerce , 4 (1), 45–64. 3. Elmagarmid, A.K. (ed.), 1992: Database Transaction Models for Advanced Appli- cations . Morgan Kaufmann, San Mateo. 4. Georgakopoulos, D., Hornick, M. and Sheth, A., 1995: An overview of workflow management. In Process Modeling to Workflow Automation Infrastructure. Distrib- uted and Parallel Databases 3, 2 (Apr. 1995), 119–152. 5. Gilman C.R., Aparicio M., Barry J., Durniak T., Lam, H. and Ramnath, R., 1997: Integration of design and manufacturing in a virtual enterprise using enterprise rules, intelligent agents, STEP, and work flow. In SPIE Proceedings on Architec- tures, Networks, and Intelligent Systems for Manufacturing Integration , pp. 160–171. 6. Gray, J. and Reuter, A., 1993: Transaction Processing: Concepts and Techniques . Morgan Kaufmann, San Mateo. 0750650885-ch005.fm Page 293 Friday, September 7, 2001 5:00 PM 294 Handbook of Production Management Methods 7. Huhns, M.N. and Singh, M.P. (eds), 1998: Readings in Agents . Morgan Kaufmann, San Francisco. 8. Jain, A.K., Aparicio, M.I.V. and Singh, M.P., 1999: Agents for process coherence in virtual enterprises, Communications of the ACM , 42 (3), 62–69. 9. Kimura, F., 1999: Virtual factory, Systems, Control and Information , 43 (1), 8–16. 10. Labrou, Y. and Finin, T., 1998: Semantics and conversations for an agent com- munication language. In M.N. Huhns and M.P. Singh (eds), Readings in Agents , Morgan Kaufmann, San Francisco, pp. 235–242. 11. Singh, M.P., 1999: An ontology for commitments in multiagent systems: Toward a unification of normative concepts, Artificial Intelligence and Law , to appear. 12. Singh, M.P., 1998: Agent communication languages: Rethinking the principles, IEEE Computer , 31 (12), 40–47. 13. Vernadat, F.B., 1996: Enterprise modeling and integration: principles and applica- tions. Chapman & Hall, London. 14. Zhou, Q. and Besant, C.B., 1999: Information management in production planning for a virtual enterprise, International Journal of Production Research , 37 (1), 207–218. 15. Zhou, Q., Souben, P. and Besant, C.B., 1998: An information management system for production planning in virtual enterprises, Computers & Industrial Engineer- ing , 35 (1), 153–156. 16. SMART. http:l/smart.npo.org/ 17. Agent Builder Environment. http:/ /www.networking.ibm.com/iag/ iagsoft.htm. Virtual manufacturing S – 3b; 4c; 8c; 11b; 13d; 14c; * 1.1b; 1.2c; 2.2b; 3.3c; 3.6c; 4.2c Virtual manufacturing is defined as manufacturing whose functionality and performance is independent of the physical distance between system elements. Virtual manufacturing is aimed at reducing product development time. Many companies understand very well that reducing product development time is a highly effective way of improving return on investment. Often the quickest route to the introduction of a new product is to select organizational resources from different companies and then synthesize them into a single business entity: a virtual company. If the various distributed resources, human and physical, are compatible with one another, that is, if they can perform their respective functions jointly, then the virtual company can behave as if it were a single company dedicated to one particular project. For as long as the market opportunity lasts, the virtual company continues to exist; when the opportunity passes, the virtual company dissolves and its personnel turn to other projects. The virtual manufacturing system is defined as an optimized manufacturing system synthesized over a universal set of primitive resources with real-time substitutable physical structure where one instantaneous physical structure has a lifetime at most as long as the lifetime of the product. The design (synthesis) and control of the system is performed in an abstract, or virtual, environment. 0750650885-ch005.fm Page 294 Friday, September 7, 2001 5:00 PM 110 manufacturing methods 295 In virtual manufacturing, a small cross-functional team is formed to stream- line the development process. The team eliminates paper drawings and carries out all design on a single CAD/CAM system, including all required computer- ized tools that may be used to improve the design of a product, production and production management. Such tools includes solid modelling, stress analysis, production line simulation and factory run-time simulation. Some of the tools are based on the virtual reality principle, which is a means of entering into a three-dimensional environment using computerized control to simulate a real environment. Some typical applications of virtual manufacturing in industry are: 1. Production design and factory planning . Virtual machines and systems model on screen all steps of new plant installation and plant operation. Engineers can plan and change plans and run and debug programs and machines. They can track workflow and create, test, and modify everything from cell models to material handling system, mimicking everything that goes on in the plant. Virtual manufacturing supports lean manufacturing; in the case of an inter- ruption, a simulation can be run on the virtual manufacturing system to find the best way to solve the problem. 2. Virtual prototyping . Virtual prototyping can significantly reduce the time and cost of building a prototype at the product specification stage. Physical models of the proposed product can be displayed on the computer monitor and examined from different view angles, and in virtual operation, thus reducing development time and improving quality. Virtual prototyping can be an integral part of concurrent engineering (CE). Personnel from all disciplines in a company (e.g. customer service, mar- keting, sales, production management, etc.) can participate in the virtual display of the proposed product, and make their comments in a quiet, clean, computerized environment. Viewing a product on screen in picture format makes it more real than detailed drawings. 3. Training and education . Training can be done by simulation. The trainee virtually performs the task he or she is being trained to do. To implement virtual manufacturing, a bridge is needed between the capabil- ities of technology and the user. There is a logical gap between what the soft- ware may offer (which is almost unlimited), and the solution algorithms, i.e. understanding the logic of operation. One of the main problems in developing virtual manufacturing is the coordination between software engineers and the real process. The software engineers who create and animate machines and systems on screen may not know enough about the limitations and pitfalls and mechanics and physics of the actual process they are planning and optimizing. They certainly do not know the unique approach of a particular plant to a given operation. Programmers 0750650885-ch005.fm Page 295 Friday, September 7, 2001 5:00 PM 296 Handbook of Production Management Methods downloading programs at the machine may have one idea about a program’s readiness, and software engineers delivering those programs for downloading may have another. The plant’s manufacturing engineers trying to get produc- tion started are, as usual, caught in the middle. They must struggle to under- stand the logic, assumptions and language of their partners in this virtual effort. Communication breakdowns due to different vocabularies and wrong assumptions, and old-fashioned cultural gaps between specialists add confu- sion, no matter how technologically advanced a project may be. Bibliography 1. Anonymous, 1998: Virtual manufacturing software covers NC machining, Manu- facturing Engineering , 120 (3), 60. 2. Cimento, A.P., 1999: What’s behind the move to ‘virtual manufacturing’, Machine Design , 71 (17), 2–4. 3. Dewey, A.M. and Bolton, R., 1999: Virtual enterprise and emissary computing technology. International Journal of Electronic Commerce , 4 (1), 45–64. 4. Giachetti, R.E., 1999: A standard manufacturing information model to support design for manufacturing in virtual enterprises, Journal of Intelligent Manufactur- ing, 10 (1), 49–60. 5. Horvath, L., Machado, J.A.T., Rudas, I.J. and Hancke, G.P., 1999: Application of part manufacturing process model in virtual manufacturing. In ISIE ‘99, Proceed- ings of the IEEE International Symposium on Industrial Electronics (Cat. No. 99TH8465). IEEE, Piscataway, NJ, 3 , 1367–1372. 6. Jain, A.K., Aparicio, M.I.V. and Singh, M.P., 1999: Agents for process coherence in virtual enterprises, Communications of the ACM , 42 (3), 62–69. 7. Kimura, F., 1999: Virtual factory, Systems Control and Information , 43 (1), 8–16. 8. Kimura, E., 1993: A product and process model for virtual manufacturing systems, Annals of the CIRP , 42 (1), 147–150. 9. Kochan, A., 1999: Virtual manufacturing comes of age, News, Boston , 54 (10), 69. 10. Pradhan, S., 1998: Virtual manufacturing information system using Java and JDBC, Computers & Industrial Engineering , 35 (1,2), 255. 11. Petrovic, D., Roy, R., Petrovic, R., 1998: Modelling and simulation of a supply chain in an uncertain environment. European Journal of Operational Research, 109 (2), 299–309. 12. Roche, C., Fitouri, S., Glardon, R. and Pouly, M., 1998: The potential of multi- agent systems in virtual manufacturing enterprises. In Proceedings Ninth Inter- national Workshop on Database and Expert Systems Applications (Cat. No. 98EX130). IEEE Computer Society, Los Alamitos, CA, pp. 913–918. 13. Smith, R.P. and Heim, J.A., 1999: Virtual facility layout design: the value of an interactive three-dimensional representation, International Journal of Production Research , 37 (17), 3941–3957. 14. Weyrich, M. and Drews, P., 1999: An interactive environment for virtual manufac- turing: the virtual workbench, Computers in Industry , 38 (1), 5–15. 15. Zhang, W.J. and Li, Q., 1999: Information modelling for made-to-order virtual enterprise manufacturing systems, Computer Aided Design , 31 (10), 611–619. 0750650885-ch005.fm Page 296 Friday, September 7, 2001 5:00 PM 110 manufacturing methods 297 16. Zhao, Z., 1998: A variant approach to constructing and managing virtual manufac- turing environments, International Journal of Computer Integrated Manufactur- ing , 11 (6), 485–499. 17. Zhou, Q., Souben, P. and Besant, C.B., 1998: An information management system for production planning in virtual enterprises, Computers & Industrial Engineer- ing , 35 (1–2), 153–156. 18. Zhiyan, Wang, Chengxiang, Gang and Zhichao, Zhang, 1999: Research on holo- graphic virtual manufacturing basis. In Proceedings 1999 IEEE International Con- ference on Robotics and Automation (Cat. No.99CH36288C). IEEE, Piscataway, NJ, 3 , 2406–2409. 19. Zhou, Q. and Besant, C.B., 1999: Information management in production plan- ning for a virtual enterprise, International Journal of Production Research , 37 (1), 207–218. 20. Zygmount, J., 1999: Why virtual manufacturing makes sense, Managing Automa- tion , 14 (1), 32–3, 36–7, 40–1. Virtual product development management (VPDM) P – 2d; 3b; 4c; 6d; 7b; 8d; 14c; 15d; * 1.2c; 1.3d; 2.1c; 2.2b; 2.3c; 2.5c; 2.6c; 3.1d; 3.2c; 4.3c See Product data management – PDM. Virtual reality for design and manufacturing T – 3b; 7c; 8c; * 1.2b; 2.1c; 2.2b; 3.3c; 3.6c; 4.2c Virtual reality (VR) technologies are used for the rapid creation, editing, analysis and visualizations of products. The application of VR to the human interaction aspect of design is a huge step in many areas of shape design and analysis, including the level of information presented to the designer, the abil- ity of the designer to interact with the design system in a free and creative manner, and the efficiency of the designer. At Ford Motor Company (Dearborn, MI), for example, the Ford 2000 initiative calls for assigning a team in a design centre anywhere in the world to work on a car platform anywhere in the world. The people who design the car work thousands of miles from the group of manufacturing engineers building it. During build and launch cycles, all parties must see, modify, and interact with the CAD data. Although the extent of the graphics was way above average it still was not enough; there’s a physical world out there that the simulations did not capture. A virtual reality-based software system developed at the University of Wisconsin-Madison includes a virtual design studio and assembly disassem- bly in three dimensions for the design and assembly/disassembly of complex artefacts. The principal notion behind these VR-based systems is to provide an 0750650885-ch005.fm Page 297 Friday, September 7, 2001 5:00 PM 298 Handbook of Production Management Methods intuitive and easy-to-use environment for engineers, designers, and others by facilitating 3D-hand tracking, voice command, and stereoscopic visual display for geometry creation, manipulation and analysis. Virtual reality technologies play a key role in virtual design and manu- facturing of artefacts for analysis or interaction tools, or both, as part of the design. Virtual assembly and disassembly involve evaluating the different aspects of a product assembly during the design phase, including assembla- bility and disassemblability, part accessibility, path planning, and subassem- bly analysis. A virtual reality-based CAD (VR-CAD) system allows concept shape designs to be created and analysed on a computer, using natural interaction mechanisms, such as voice and hand action/motion. As opposed to the Windows–Icons–Menu–Pointer paradigm, common to most CAD systems, the VR-CAD system is based on the Work Space–Instance–Speech–Locator approach. In a VR-CAD system, the designer creates three-dimensional appliance/ product shapes by voice commands, hand motions, and finger motions. The designer grasps objects with his/her hands and moves them around, and detaches parts from assemblies and attaches new parts to assemblies for virtual manufacturing analysis. Virtual reality devices enable such intuitive interactions and thereby allow a designer with a minimum level of experience of using a CAD system to create and analyse concept shapes quickly and efficiently. Shape creation systems may provide a hierarchical representation that allows high-speed editing of 3D shapes in a virtual environment. To facilitate shape design, this representation allows enforcement of design rules and provides other features, such as intelligent dimensioning to further speed up the task of shape creation. In addition to the parametric component/assembly design, a hierarchical representation for displaying and editing freeform models has been developed. By combining different input modalities, such as voice and hand inputs, the designer can effectively create the design shape by talking to the system through the voice command and manipulating objects in the design space via hand action and motion. Virtual assembly – disassembly systems, may perform virtual assembly and disassembly analysis of 3D geometric models. A system may generate, animate, edit, and validate the assembly–disassembly sequences and paths for appliance/product subassemblies. In addition, the user can perform several other virtual manufacturing analyses, such as interception checking, clearance checking, accessibility analysis of components and design rule checking. Concurrent engineering systems can be used whereby different engineers at the same or different location can share, modify, and discuss the assembly/ appliance design. Evaluation of an appliance assembly provides the user with the information regarding the feasibility of assembling the components, the 0750650885-ch005.fm Page 298 Friday, September 7, 2001 5:00 PM 110 manufacturing methods 299 accessibility of the components, and the sequence to assemble the components in an appliance assembly. Virtual reality allows determination of the sequence and cost of disassem- bling/assembling components for appliance maintenance. In turn, the designer may perform design changes to facilitate ease of assembly/disassembly for maintenance. Virtual reality allows determination of the maximal profitable disassembly sequence for separating components of different materials. Maximizing the recycling profit results in greater impetus for companies to recycle an appliance. Bibliography 1. Bick, B., Kampker, M., Starke, G. and Weyrich, M., 1998: Realistic 3D-visualisation of manufacturing systems based on data of a discrete event simulation. In IECON ’98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.98CH36200). IEEE, New York, 4 , 2543–2548. 2. Giachetti, R.E., 1999: A standard manufacturing information model to support design for manufacturing in virtual enterprises, Journal of Intelligent Manufactur- ing , 10 (1), 49–60. 3. Lu, C.J.J., Tsai, K.H., Yang, J.C.S. and Yu, Wang, 1998: A virtual testbed for the life-cycle design of automated manufacturing facilities, International Journal of Advanced Manufacturing Technology , 14 (8), 608–615. 4. Smith, R.P. and Heim, J.A., 1999: Virtual facility layout design: the value of an interactive three-dimensional representation, International Journal of Production Research, 37 (17), 3941–3957. 5. Tseng, M.M., Jianxin, J. and Chuang, J.S., 1998: Virtual prototyping for custom- ized product development, Integrated Manufacturing Systems , 9 (6), 334–343. 6. Zamfirescu, C.B., Barbat, B. and Filip, F.G., 1998: The ‘coach’ metaphor in CSCW decision making system design. In Intelligent Systems for Manufacturing: Multi-Agent Systems and Virtual Organizations. Proceedings of the BASYS’98– 3rd IEEE/IFIP International Conference on Information Technology for Balanced Automation Systems in Manufacturing . Kluwer Academic Publishers, Norwell, MA, pp. 241–250. 7. VDS, I-CARVE Lab, http://icarve.me.wisc. edu/groups/virtual 8. A3D, I-CARVE Lab, http:/ icarve. me. wisc. edu/groups/disassembly 9. I-CARVE Lab, UW-Madison, http://icarve. me. wisc. edu 10. CAD-IT Consortium, UW-Madison, http:/ /cad-it.me.wisc. edu Virtual reality P – 2c; 3c; 4d; 8d; 9b; 10c; 13c; * 1.1b; 1.2b; 1.3c; 1.6d; 2.2b; 3.2c; 3.3c; 4.1b; 4.2c Virtual reality provides major opportunities to simplify the way we commu- nicate and run applications, and so improve business processes without costing a large amount of money. 0750650885-ch005.fm Page 299 Friday, September 7, 2001 5:00 PM [...]... 2001 5:00 PM 300 Handbook of Production Management Methods Improved time-to-market and increased information share are just a couple of advantages offered by current simulation and virtual reality packages Recent advances in simulation software have focused on three main areas – ease of use, enhanced visualization, and ease of interpretation Consequently, companies are widening the use of simulation within... 1994: The management of manufacturing flexibility, California Management Review, 36(2), 72–89 14 Upton, D.M., 1995: What really makes factories flexible? Harvard Business Review, 73(4), 74–84 15 Vickery, S.K., 1991: A theory of production competence revisited, Decision Sciences, 22(3), 635–643 0750650885-ch005.fm Page 310 Friday, September 7, 2001 5:00 PM 310 Handbook of Production Management Methods. .. three main areas The first area is management: 1 2 3 4 Leadership with vision Create goals and new ways of thinking Prepare a long-range strategic plan, and work it out Employee participation in company operations and problem solving 0750650885-ch005.fm Page 308 Friday, September 7, 2001 5:00 PM 308 Handbook of Production Management Methods 5 6 7 8 9 Clear definition of overall integrated goals Create... reused, instead of creating waste It might increase the initial cost, but it will pay at the product end of life Processes must be selected such that they create the least amount of waste Recycling concepts, as they are required in actual waste management legislation, often need the development of disassembly processes to assure efficient separation of hazardous materials, or the accumulation of ingredients... (CAPP) 98, 117 , 176 Computer Integrated Manufacturing (CIM) 8, 62, 101 Computer Oriented PICS (COPIS) 5, 112 Computer Numerical Control (CNC) 83, 160 Concurrent Engineering (CE) 105, 121, 298 Constant work in process (CONWIP) 109 Constraints management 90 Continuous logic 165 Cooperative manufacturing 111 Computer Oriented PICS (COPIS) 5, 112 Core competence 114 Cost accounting 59 Cost estimation 117 Crosby... factor in workflow management, it is important to use an established framework for modelling and analysing workflow processes The various forms of interoperability are as follows Capacity sharing – This form of interoperability assumes centralized control, i.e the routing of the workflow is under the control of one workflow manager The execution of tasks is distributed, i.e the resources of several business... Lawrence, P (ed.), 1997: Workflow Handbook 1997, Workflow Management Coalition John Wiley and Sons, New York 8 Murata, T., 1989: Petri nets: properties, analysis and applications Proceedings of the IEEE, 77(4), 541–580 9 WFMC, 1996: Workflow Management Coalition Terminology and Glossary (WFMC-TC-1 011) Technical report, Workflow Management Coalition, Brussels 10 WFMC, 1996: Workflow Management Coalition Standard... Systems and Virtual Organizations Proceedings of the BASYS’98–3rd IEEE/IFIP International Conference on Information Technology for Balanced Automation Systems in Manufacturing Kluwer Academic Publishers, Norwell, MA, pp 171–184 0750650885-ch005.fm Page 302 Friday, September 7, 2001 5:00 PM 302 Handbook of Production Management Methods 8 McLean, C., 1997: Production system engineering using virtual manufacturing... regardless of its magnitude, ultimately leading to an impairment of the overall achievement of improvement plans Another theme that is recurrent in many BPR approaches is the presence of information technology as an enabler of solutions In sharp contrast, WCM programs are commonly opposed to information solutions 0750650885-ch005.fm Page 309 Friday, September 7, 2001 5:00 PM 110 manufacturing methods. .. Annals of the CIRP, 43(1), p 9 Workflow management M – 3c; 6b; 7a; 13a; * 1.1b; 1.6d; 3.2d; 3.3b; 3.5b; 4.1b; 4.2b; 4.3b; 4.4c Workflow management focuses on improving the effectiveness and efficiency of businesses processes within an organization Interorganizational workflow offers companies the opportunity to re-shape business processes beyond the boundaries of individual organizations Workflow management . 290 Handbook of Production Management Methods 8. Niessink, F. and Van-Vliet, H., 1999: Measurements should generate value, rather than data [software metrics]. In Proceedings. PM 292 Handbook of Production Management Methods 9. Schneider, J.G., Boyan, J.A. and Moore, A.W., 1998: Value function based produc- tion scheduling. In Machine Learning. Proceedings of the. the design of a product, production and production management. Such tools includes solid modelling, stress analysis, production line simulation and factory run-time simulation. Some of the tools