Production planning and scheduling using integrated data structures in ERP: Implementation and numerical simulation

Abstract

This paper aims to address limitations with existing data structures and associated production planning and scheduling methods in enterprise resource planning (ERP). The methodology consists of: (i) the development of a theoretical framework of integrated data and associated planning and scheduling methods, (ii) the implementation of integrated data in ERP, and (iii) the development of a model for evaluating the impact of slack times on lead-time using existing data structures. Integrated data using additional relationships provide the capabilities of simultaneous and forward planning of various data elements (materials, activities, operations and resources) and finite leading of resources. Numerical simulation shows that planning of integrated data results in shorter lead-times than has been traditional. Furthermore, it is noted that integrated data with graphical display enables data maintainability, flexibility and transparency for better planning and scheduling. Furthermore, the number of assemblies and the size of operations routings at each bill of materials level have been identified as key factors impacting on production planning and scheduling, in particular lead-times. Despite implementation of integrated data in an ERP, numerical simulation is limited to one product structure and represents only a snapshot of planning and scheduling results. Thus, future research is being planned for the simulation of a large assembly network using a case from industry. This research advances understanding of the limitations of existing data in ERP and proposes an approach for overcoming some of these limitations by using integrated data.

Keywords::

• planning and scheduling
• bill of materials
• operations routing
• data structures
• lead-time

JEL Classification::

• M110
• C35

Funding

The authors wish to acknowledge the financial support provided by the College of Business, University of Western Sydney, through the Business Process Evolution Studies (BPES) Research Node; the Higher Education Research Promotion and National Research University Project of Thailand, Office of the Higher Education Commission; Thammasat University.