Case studies in implementing dynamic production planning and scheduling system in make-to-order high-mix-low-volume small and medium-scaled industries for production efficiency

• Main Authors: Lim, Teck Loon, Kow, Mee Yee, Abu Bakar, Nooh, Yip, M. W.
• Format: Conference or Workshop Item
• Language: English
• Published: 2014
• Subjects: T Technology (General)
• Online Access: http://eprints.utm.my/id/eprint/61012/1/NoohAbuBakar2014_CaseStudiesinImplementingDynamicProductionPlanning.pdf; http://eprints.utm.my/id/eprint/61012/
• Institution: Universiti Teknologi Malaysia

To manage a high-mix manufacturing environment efficiently is a big challenge for the small and medium-scaled industries (SMIs) because of the nature of its dynamic and ever changing production environment. This has added extra challenges for the SMIs to adopt the right and suitable computerized system for improvement. This paper reviews the implementation of computerized planning and scheduling system to the make-to-order (MTO) high-mix-low-volume (HMLV) SMIs to overcome their daily production challenges in managing the products, processes and resources. Investigation has been conducted in two local manufacturing companies to study the effectiveness of implementing the planning and scheduling system that has brought improvement to the MTO HMLV production environment. The research was conducted in mixed mode of qualitative and quantitative methods after the software being implemented for a year. The findings show the implementation of the system that can bring improvements overall. However, there are some other challenges not related to the software have been discovered such as human factors. The issues are listed in discussion section. The outcome of this research will accrue to manufacturers through an improved understanding of the operation and performance of implementing the system. The authors recommend further research works to be carried out to determine the other key success factors for MTO HMLV SMIs to implement computerize system to improve overall production efficiency.