Development of Product Resource Inventory Control Using Forecasting In ‘SMED’

Authors

  • Wei Jie Woon Faculty of Manufacturing Engineering, Universiti Malaysia Pahang, 26600, Pekan, Pahang, Malaysia
  • Siti Zubaidah Ismail Faculty of Manufacturing Engineering, Universiti Malaysia Pahang, 26600, Pekan, Pahang, Malaysia

DOI:

https://doi.org/10.15282/jmmst.v1i1.202

Keywords:

PSS, Forecasting, Industry 4.0, Inventory control, SMED

Abstract

Industry 4.0 known as “Fourth Industrial Revolution” and also “smart manufacturing” is the current trend of the manufacturing organization. There are four main components for Industry 4.0 which are Internet of Things (IoT), Cyber Physical Systems (CPS), Internet of Services (IoS) and Smart Factory. Product service system (PSS) is a system that combine product and service; to fulfill customer demand and increase their satisfaction level. The main objective of inventory control is to prevent storage overload and ensure storage always have sufficient supply for the customer. By adding sensor, the inventory in storage can be counted and controlled. The output from the sensor can be displayed on the computer and the operator can look out the storage status. Forecasting in inventory can predict the trend of the inventory in future. This allow operator to keep tracking on their reorder point and make sure the inventory never run out.

References

Vandermerwe, S. and Rada, J. (1988), “Servitization of business: adding value by adding services”, European Management Journal, Vol. 6 No. 4.

Brady, T., & Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organization Studies, 25(9), 1601.

Szwejczewski, M., Goffin, K., & Anagnostopoulos, Z. (2015). Product service systems, after-sales service and new product development. International Journal of Production Research, 53(17), 5334–5353.

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Published

13-09-2018

How to Cite

Woon, W. J., & Ismail, S. Z. (2018). Development of Product Resource Inventory Control Using Forecasting In ‘SMED’. Journal of Modern Manufacturing Systems and Technology, 1, 82–93. https://doi.org/10.15282/jmmst.v1i1.202

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