Integration of Production Scheduling, Inventory Control and Maintenance Planning in Multi-machine Manufacturing Systems | Shiv Nadar University
Enquire Now
Apply Now
Undergraduate AdmissionsUndergraduate Information SessionInternational AdmissionsM.Tech / PG ProgramsPhD Admission Monsoon 2022MBA Degree ProgramMBA (Executive) AdmissionsMBA (Online) AdmissionsData Sciences and Analytics for Business (DSAB)

Integration of Production Scheduling, Inventory Control and Maintenance Planning in Multi-machine Manufacturing Systems

In the present scenario, manufacturing industries are facing pressure for improving their performance in terms of continuous production, improved quality, low cost and fast delivery of goods, which has forced the production and delivery processes to be highly reliable. It is evident that the performance of any manufacturing system strongly depends on the performance at the shop floor level.  For shop floor operations to be efficient, it is important to have proper maintenance planning decisions, control over inventory management and sound production scheduling methodologies. However, these three aspects of operations planning also have an interaction effect on each other and hence a joint optimization of scheduling, inventory, and maintenance provides improvisation that is even more significant over conventional approaches. Despite the awareness about possible interaction effect, many industries fail to utilize the integrated approaches effectively and efficiently in order to maximize their performance. This may be due to the reason that the present approaches of joint optimization planning are still at an exploratory stage as most of the integrated models ponder several unrealistic assumptions such as single machine system, ignorance of inventory costs, fixed maintenance interval, computational complexities, etc. 

With the motivation to further improve the economic performance of the shop floor system, the present research aims to provide an integrated model of production scheduling, inventory control and maintenance planning in multi-machine manufacturing systems by modeling and quantifying the interdependencies among them. This research attempts to provide a dynamic approach of joint optimization by relaxing the unrealistic assumptions to the maximum possible extent so that it can be applied to practical situations. An integrated mathematical model to encompass the features of scheduling, inventory and maintenance is developed and an effort is made to identify the key performance indicators, which would alter the effectiveness of a manufacturing system. In order to optimize the proposed problem, two novel, and efficient optimization techniques namely teaching-learning based optimization (TLBO) algorithm and Jaya algorithm are proposed which provide optimum solutions with the increased solution and computational efficiency. The efficacy of the proposed integrated approach is evaluated by comparing the results with the isolated models. A systematic sensitivity analysis of various models is also performed. The emphasis of this dissertation is on providing a methodology for the integration of production scheduling, inventory control and maintenance planning decisions and investigating the benefits of joint optimization of these policies in terms of the expected total cost per unit time.

Department: 
Mechanical Engineering
Year: 
2020
Student Name: 
Aseem Kumar Mishra
Faculty Advisor: 

Directions