Modelling the dynamics of inventory and backlog management in servitized supply chains: The case of custom industrial manufacturing girms
An important challenge for managers in a servitized supply chain is to integrate the delivery of the products and services such that resources and knowledge are used effectively and efficiently. In the absence of a study that simultaneously considered the various services rendered at different stage...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | text |
| Published: |
Animo Repository
2019
|
| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/2096 https://animorepository.dlsu.edu.ph/context/faculty_research/article/3095/type/native/viewcontent |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | De La Salle University |
| Summary: | An important challenge for managers in a servitized supply chain is to integrate the delivery of the products and services such that resources and knowledge are used effectively and efficiently. In the absence of a study that simultaneously considered the various services rendered at different stages of the product life of a servitized manufacturing firm, this study developed a system dynamics simulation model that incorporates the product and service operations of a custom industrial manufacturing firm and the response of the customers in the firm's service level to analyze the effectiveness of various service capacity and inventory strategies. From the insights generated in the results and analysis, alternative policies that target the major feedback loops were generated. The policies include incorporating manufacturing and service capacity utilization decisions, and a dynamic safety stock decision. These policies were proven to improve the overall system behavior by significantly attenuating the amplifications, phase lags, and oscillations in all subsystems of the servitized supply chain, while maintaining desirable service levels. The theoretical findings were then translated tomanagerial implications. © 2019 IEEE. |
|---|