Worker-machine relationship based strategy for sustainable management in a machine shop
Department/Unit
Vice Chancellor for Laguna Campus
Document Type
Conference Proceeding
Source Title
RSF Conference Series: Business, Management, and Social Sciences
Volume
2
Issue
1
First Page
155
Last Page
165
Publication Date
2022
Abstract
Nowadays, establishing a sustainable management plan will help organizations use resources effectively and efficiently and help the business to have a competitive advantage in the long term. In a machine shop where the operation cost is high and resources are not effectively used, a worker-machine relationship-based strategy has been introduced. Many studies explored the use of different problem solving tools in different fields, however there is a lack of studies in the application of gang process chart, random and synchronous servicing especially in machine shop. Thus, the purpose of this study was to evaluate the job distribution during service operation, to determine which worker and machine will require reassignment to operate effectively, and lastly propose a sustainable management strategy to optimize the operation and reduce the operation cost. This study used a descriptive research design with an overt observational approach in a well-established machine shop in Oriental Mindoro, Philippines. A total of fifteen operators who were directly involved with the machines have been observed. The study discovered that Operators 1,2,3.4 and 5 are already operating on the ideal number of machines, Operator 6 will require one more additional machine, Operator 7,8 9 and 10 will require one less machine to operate on an ideal number and save operation cost.
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Recommended Citation
Dalisay, S. R., Alagos, A. D., Saflor, C. R., Marinas, K., & Jou, Y. (2022). Worker-machine relationship based strategy for sustainable management in a machine shop. RSF Conference Series: Business, Management, and Social Sciences, 2 (1), 155-165. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/13801
Disciplines
Operations Research, Systems Engineering and Industrial Engineering
Keywords
Machine shops—Management; Sustainability
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