PRIORITIZATION AND EFFICIENT ROUTE SELECTION IN AUTOOTIVE PARTS MANUFACTURING

Abstract

Scheduling automotive part manufacturing is a more arduous and complex task. It is a very backbreaker task to get an optimum schedule for any automotive part manufacturing. In today’s scenario, every industry and research organization need an energy-efficient system to cope up with the global environment. In this study, a first-time energy-efficient fuzzy scheduling system is developed for crankcase cover manufacturing under uncertain processing times. This study consists of the development of an energy-efficient fuzzy inference system of the four-crankcase cover (cover left side crankcase KWPG, cover left crankcase K38, cover crankcase 206 G, and cover right crankcase KTE) and its results are validated by the fuzzy set approach. Fuzzy logic provides a decision by a combination of the rules for selecting job priorities and route selection. This scheduling system also provides the trade-off between energy consumption and makespan. This study also deals with the identification of the best material for crankcase cover manufacturing. To satisfy customer needs, designers must predict the performance of all available materials and find out the best material for the product. Since the various materials are available in the market with diverse characteristics, which makes the material selection process is complex. So, there is an indispensable need for a proper material selection methodology. The designers must identify the best approach which enhanced the product performance and reduced the time of designing. In this study, the first-time selection of materials for a two-wheeler crankcase cover is done using integrated TOPSIS PROMETHEE, and MOORA model. The final rankings of alternatives obtained from this novel proposed model are also compared with each other for finding the best material for crankcase cover. The research also focuses on the multi-objective single-machine static scheduling problems of motorcycle crankcase cover. To solve these single-machine static scheduling problems, dispatching rules are used. Various dispatching rules used in this study are EDD, SPT, CR, LPT, WSPT, COVERT, and Hodgson’s algorithm. This study helps us to obtain optimal job prioritization of two-wheeler crankcase covers in the automobile industry. Results show that shifting the production system from WSPT approach scheduling to the EDD scheduling approach; minimizes the mean flow time, weighted mean flow time, and maximum lateness. The Automotive industry is one of the biggest emerging sectors in terms of revenue. Every automotive industry has an indispensable need for optimum manufacturing scheduling systems for generating good revenues and profits. This need can be pulled off by xviii identifying and prioritizing the scheduling parameters also. MCDM is one of the best techniques of operation research in selecting the best parameters or factors among the various alternatives. This study includes the identification and prioritization of the various important scheduling parameters in the Indian automotive industry. The twelve scheduling parameters have been identified in this study and these parameters are prioritized by the fuzzy-TOPSIS and DEMATEL model. These methods best deal with uncertainty and vagueness. The first time, fuzzy TOPSIS and DEMATEL are applied in prioritizing the SPs in the automobile industry. The expert’s views are gathered from the five automobile industries. Makespan, energy consumption, due date, and travel time are the crucial parameters obtained using fuzzy TOPSIS. The least important parameters obtained using fuzzy TOPSIS are work in process, flow time, and release date. The most influential parameters identified using the DEMATEL method are completion time and processing time. This study is very useful for all automotive industries as well as research organizations. This study also deals with the development of a simulation model of crankcase cover manufacturing. The simulation creates the virtual production model which is exactly like the real environment, and it provides future insights before laying down the actual production plant layout. With the help of simulation, we can simulate the complex and costly manufacturing system without being investing money physically and check the system’s real-life behavior. In this study, the modelling and simulation of two-wheeler crankcase cover manufacturing are done with the help of flexsim. This study deals with the development of a simulation model for crankcase cover manufacturing systems in the automobile industry. Flexsim simulation tool is used as an optimization tool for identifying the bottleneck present in the production line to improve the system performance and line efficiency. The results indicate that by eliminating the bottleneck in the production line, it increases the line efficiency as well as the production throughput. These results are useful for all industries for simulating their process or product layout.