Research Article
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A Dynamic Approach In Production Management for Automotive Field

Year 2020, Volume: 4 Issue: 2, 53 - 58, 20.06.2020
https://doi.org/10.26701/ems.678821

Abstract

Solution proposals, based on dynamic approaches, can easily take place of the existing situations owing to the unlimited customer requests. Therefore, this may lead to a rapid transformation, triggering the manufacturing society to deal with the requirements for a sustainable competitive advantage.

Especially, the automotive field, deeply affected by the fast-changing demands, brings about some new business models superimposing the existing ones because of the technology-intensive production management. This progress makes the world’s expectation be higher depending on process innovation and minimizing the lead time may be declared as one of the top satisfaction points in the market.

This paper, including the review of different manufacturing methods, highlights the awareness of the best implementations along with the production management in the automotive field. Moreover, it aims to develop a process innovation by designing a dynamic algorithm. The content of the paper, depending on multiple machines with multiple orders, is completed in all details by analyzing the gaps of the literature review. In the second step, the original algorithm is formed by taking into consideration the priorities. The achieved analysis is based on the main criteria and subcomponents of the scheduling of the manufacturing process. Finally, the algorithm, formed by four main priorities, leads the numerical implementations to be done in only one order and the results show that this approach can be a good way for minimization of total delays of orders.

References

  • Panwalkar, S.S., Iskander. W., (1977) A survey of scheduling rules, Operations research 25.1, 45-61.
  • Sun, D., Lin, L., (1994) A dynamic job shop scheduling framework: a backward approach. The International Journal of Production Research, 32(4), 967-985.
  • Tjornfelt-Jensen, M., Hansen, T. K., (1999) Robust solutions to job shop problems. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 IEEE (Cat. No. 99TH8406) 2, 1138-1144.
  • Duenyas, I., Van Oyen, M. P., (1996). Heuristic scheduling of parallel heterogeneous queues with set-ups. Management Science, 42(6), 814-829.
  • Banerjee, S., Banerjee, A., Burton, J., Bistline, W., (2001) Controlled partial shipments in two-echelon supply chain networks: a simulation study. International Journal of Production Economics, 71(1-3), 91-100.
  • Godin, V. B. (1978). Interactive scheduling: historical survey and state of the art. AIIE Transactions, 10(3), 331-337.
  • Vancheeswaran, R., Townsend, M. A., (1993) Two-stage heuristic procedure for scheduling job shops. Journal of Manufacturing Systems, 12(4), 315-325.
  • Blackstone, J. H., Phillips, D. T., Hogg, G. L., (1982) A state-of-the-art survey of dispatching rules for manufacturing job shop operations. The International Journal of Production Research, 20(1), 27-45.
  • Buxey, G., (1989) Production scheduling: Practice and theory. European Journal of Operational Research, 39(1), 17-31.
  • Metaxiotis, K. S., Askounis, D., & Psarras, J., (2002), Expert systems in production planning and scheduling: A state-of-the-art survey. Journal of Intelligent Manufacturing, 13(4), 253-260.
  • Kerr, R., & Ebsary, R., (1988), Implementation of an expert system for production scheduling. European journal of operational research, 33(1), 17-29.
  • Righettini, P., & Strada, R., & Gosatti, A., & Togni, S., & Camozzi, F., & Fissore, C. (2019), Smart Mobility: a modern approach to automotive product development for vehicle electrification IEEE 5th International forum on Research and Technology for Society and Industry (RTSI), 459-464.
  • Qamar, A., Hall, M. A., & Collinson, S. (2018), Lean versus agile production: flexibility trade-offs within the automotive supply chain. International Journal of Production Research, 56(11), 3974-3993.
Year 2020, Volume: 4 Issue: 2, 53 - 58, 20.06.2020
https://doi.org/10.26701/ems.678821

Abstract

References

  • Panwalkar, S.S., Iskander. W., (1977) A survey of scheduling rules, Operations research 25.1, 45-61.
  • Sun, D., Lin, L., (1994) A dynamic job shop scheduling framework: a backward approach. The International Journal of Production Research, 32(4), 967-985.
  • Tjornfelt-Jensen, M., Hansen, T. K., (1999) Robust solutions to job shop problems. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 IEEE (Cat. No. 99TH8406) 2, 1138-1144.
  • Duenyas, I., Van Oyen, M. P., (1996). Heuristic scheduling of parallel heterogeneous queues with set-ups. Management Science, 42(6), 814-829.
  • Banerjee, S., Banerjee, A., Burton, J., Bistline, W., (2001) Controlled partial shipments in two-echelon supply chain networks: a simulation study. International Journal of Production Economics, 71(1-3), 91-100.
  • Godin, V. B. (1978). Interactive scheduling: historical survey and state of the art. AIIE Transactions, 10(3), 331-337.
  • Vancheeswaran, R., Townsend, M. A., (1993) Two-stage heuristic procedure for scheduling job shops. Journal of Manufacturing Systems, 12(4), 315-325.
  • Blackstone, J. H., Phillips, D. T., Hogg, G. L., (1982) A state-of-the-art survey of dispatching rules for manufacturing job shop operations. The International Journal of Production Research, 20(1), 27-45.
  • Buxey, G., (1989) Production scheduling: Practice and theory. European Journal of Operational Research, 39(1), 17-31.
  • Metaxiotis, K. S., Askounis, D., & Psarras, J., (2002), Expert systems in production planning and scheduling: A state-of-the-art survey. Journal of Intelligent Manufacturing, 13(4), 253-260.
  • Kerr, R., & Ebsary, R., (1988), Implementation of an expert system for production scheduling. European journal of operational research, 33(1), 17-29.
  • Righettini, P., & Strada, R., & Gosatti, A., & Togni, S., & Camozzi, F., & Fissore, C. (2019), Smart Mobility: a modern approach to automotive product development for vehicle electrification IEEE 5th International forum on Research and Technology for Society and Industry (RTSI), 459-464.
  • Qamar, A., Hall, M. A., & Collinson, S. (2018), Lean versus agile production: flexibility trade-offs within the automotive supply chain. International Journal of Production Research, 56(11), 3974-3993.
There are 13 citations in total.

Details

Primary Language English
Subjects Mechanical Engineering
Journal Section Research Article
Authors

Banu Özkeser 0000-0002-0289-1674

Publication Date June 20, 2020
Acceptance Date February 26, 2020
Published in Issue Year 2020 Volume: 4 Issue: 2

Cite

APA Özkeser, B. (2020). A Dynamic Approach In Production Management for Automotive Field. European Mechanical Science, 4(2), 53-58. https://doi.org/10.26701/ems.678821
AMA Özkeser B. A Dynamic Approach In Production Management for Automotive Field. EMS. June 2020;4(2):53-58. doi:10.26701/ems.678821
Chicago Özkeser, Banu. “A Dynamic Approach In Production Management for Automotive Field”. European Mechanical Science 4, no. 2 (June 2020): 53-58. https://doi.org/10.26701/ems.678821.
EndNote Özkeser B (June 1, 2020) A Dynamic Approach In Production Management for Automotive Field. European Mechanical Science 4 2 53–58.
IEEE B. Özkeser, “A Dynamic Approach In Production Management for Automotive Field”, EMS, vol. 4, no. 2, pp. 53–58, 2020, doi: 10.26701/ems.678821.
ISNAD Özkeser, Banu. “A Dynamic Approach In Production Management for Automotive Field”. European Mechanical Science 4/2 (June 2020), 53-58. https://doi.org/10.26701/ems.678821.
JAMA Özkeser B. A Dynamic Approach In Production Management for Automotive Field. EMS. 2020;4:53–58.
MLA Özkeser, Banu. “A Dynamic Approach In Production Management for Automotive Field”. European Mechanical Science, vol. 4, no. 2, 2020, pp. 53-58, doi:10.26701/ems.678821.
Vancouver Özkeser B. A Dynamic Approach In Production Management for Automotive Field. EMS. 2020;4(2):53-8.

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