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Norhaslinda Zainal Abidin
Universiti Utara Malaysia
Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering Transportation

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Predicting Completion Time for Production Line in a Supply Chain System through Artificial Neural Networks Ahmad Afif Ahmarofi; Razamin Ramli; Norhaslinda Zainal Abidin
International Journal of Supply Chain Management Vol 6, No 3 (2017): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (13.161 KB)

Abstract

Completion time in manufacturing sector is the time needed to produce a product through production processes in sequence and it reflects the delivery performance of such company in supply chain system to meet customer demands on time. However, actual completion time always deviated from the standard completion time due to unavoidable factors and consequently affect delivery due date and ultimately lead to customer dissatisfaction. Therefore, this paper predicts completion time based on historical data of production line activities and discovers the most influential factor that contributes to the tardiness or a late jobs due date from its completion time. A well-known company in producing audio speaker is selected as a case company. Based on the review of previous works, it is found that Artificial Neural Networks (ANN) has superior capability in prediction of future occurrence by capturing the underlying relationship among variables through historical data. Besides, ANN is also capable to provide final weight for each of related variable. Variable with the highest value of final weight indicates the most influential variable and should be concerned more to solve completion time issue which has persisted among entities in supply chain system. The obtained result is expected to become an advantageous guidance for every entity in supply chain system to fulfil completion time requirement as requested by customer in order to survive in this turbulent market place.
A Simulation-Based Optimization Framework for Improving Customer Waiting Time During Vehicle Inspection Process Khibtiyah Ilyas; Norazura Ahmad; Norhaslinda Zainal Abidin
International Journal of Supply Chain Management Vol 8, No 1 (2019): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

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Abstract

Issue of long customer waiting time is a common issue at service industry. A Vehicle Inspection Centre (VIC) is one of the service industries that faces this issue and has a significant impact on quality of service. The management of VIC has been struggling in applying alternative solutions to reduce the customer waiting time, but the long customer waiting time still occurs. Therefore, the management requires an appropriate tool that contributes to improve customer waiting time problem and indirectly improving quality of service. To assist the management, a simulation-based optimization framework is presented in this paper to mitigate the issue of long customer waiting time. The preliminary result of the implementation of the framework on customer waiting time at VIC is also presented in this paper.
Co-Authors Ahmad Afif Ahmarofi Khibtiyah Ilyas Norazura Ahmad Razamin Ramli