Production planning and inventory management of job shop systems

Abstract

In the present day global competition, there is tremendous pressure on every manufacturing and service system to perform at peak efficiency so that the price of the products could be kept at a low level. The pressure is exacerbated by the fact that the modern day customers want variety of product models. It is well known that increase in product variety increases complexities, and decreases the efficiency of the system. The manufacturing/service system thus has to simultaneously deal with high product variety and along with high levels of productivity. This has lead to increased application of modern manufacturing practices in high variety production systems called job shop production system. A particular industrial sector which has attracted much interest due to its fast growth, complex manufacturing and highly demanding after sales service system; is the automobile industry. Customer perceptions of the vehicle and the manufacturer evolve during vehicle ownership, and depend upon both vehicle and after-sales services. Considering the Indian economy, automotive sector is one of its major contributors. Owing to large variety of models, expensive infrastructure and demanding customers, the complexities involved in the management of Automobile Service Centre (ASC) is increasing. Here each vehicle enters the ASC with different repair and service need; and hence resembles job shop system. Along with features of job shop production (JSP), ASC has several common features with supply chain management (SCM), maintenance management (MM) and service management(SM). Various aspects of MM like reliability, breakdown and preventive maintenance are involved. Since automobile repair shops are service shops where customer is directly involved, so many theories of SM like customer satisfaction and service quality are applicable for ASC. Along with JSP, MM and SM issues, dimensions of supply chain management of spare parts management need to be looked while managing service centres. In spite of significant contribution of ASC‘s in the growth of automotive sector, very less research attention is given to this area. An attempt has been made in this study to fill the gaps in contemporary research in context with complex job shops like ASC. The study aims to locate key research issues of JSP to study service rate and utilization. The performance measures, critical success factors and decision variables are to be found. With this information, simulation model of ASC is to be developed and the performance of existing system is to be analyzed. The present research is intended to develop performance scenario under different internal and external changes like capacity constraints and varying demand. The study also aims to develop models using techniques like Artificial Neural Network (ANN), Analytical Hierarchy Process (AHP), and Analytical Network Process (ANP) etc to study the inter relationship between critical success factors. The ASC chosen for purpose of this study is located in northern part of India. Data is collected from authorized ASC in terms of processing time and sequence. Based on the information, simulation model of ASC is developed using simulation package Witness 2006 provided by lanner group. The simulation experiments were conducted to perform capacity planning and study the effects of demand variability on performance measures of ASC. This is beneficial to find the impact of demand variability in the system performance and develop a framework for system design to proactively incorporate consideration of variability in all forms in the design stage. The parameter optimization is done using Taguchi design of experiments (DOE). The study presents ANN decision support system for spare parts management of ASC and helps to predicts reorder point and order quantity. The research strategies for performance improvement are formulated by finding the inter relationship between various critical success factors using ISM. The best strategy is chosen using ANP technique. The dimensions are taken from four perspectives of balanced scorecard approach suggested by Kaplan and Norton and hence link financial and non financial; tangible and non tangible; internal and external factors. This provides holistic approach for conducting the research. The present study provides the comprehensive literature review and identifies contemporary research issues related to systems like ASC, which has integrated features of JSP, MM, SCM and SM. With the help of simulation experiments, various policies to meet the conditions of demand variability are designed. Also, optimum parameter factors are found and their effects on critical performance measures are studied. A framework incorporating spare part management, using ANN, is presented to forecast reorder point and ordered quality of repair parts. The analysis considers parameters like unit price, annual demand etc other than inventory holding cost and carrying cost. This forecasting of demand of spare parts will be helpful in improving the service level and on time delivery of service to the customers.The foundation for developing the strategies for performance improvement is presented in this work using ISM. ANP method with balanced score approach is developed to find the best alternatives for development and selection of appropriate operational strategy for improving the overall performance of the service system. The research reported in this thesis attempts to provide the guidelines to establish policy for performance improvement on the shop floor. These guidelines will help to develop the strategies for performance improvement. The strategies can be applied to similar job shops like mobile repair, two wheeler repair shop and service centres of metro, computers, home appliances etc.