Detection of Bottleneck in Manufacturing Supply Chain using Specific KPI

12 pages•Published: September 20, 2022

Yoshiatsu Kawabata, Yuta Hosokawa and Katsuhide Fujita

Abstract

With the introduction of the Digital Transformation (DX) era, It is now feasible to obtain digital data not only on the shop floor of the manufacturing facility but also across the whole supply chain (SC) network for improved management. The Bottleneck (BN) is the first tackling point to gain more throughput. By getting the accumulated Lead time (LT) data on the SC network map using simulations, we could identify the SC bottleneck regardless of the production policies such as push or pull: using a simulator that imitates the production of the entire SC network by assembling the materials; using the simple Key Performance Indicators (KPIs) that are the average lead time and the standard deviation of lead time on the simulator; identifying the BN from the remaining quantities of work in processes (WIP) between the nodes in a high-demand situation; identifying the BN based on the use of nodes at the low-demand situation virtually. In addition, our last method can depict the degree how each node is close to the BN, by sorting the rate of the utilization of the nodes.

Keyphrases: bottleneck, lead time, simulator, supply chain

In: Tokuro Matsuo (editor). Proceedings of 11th International Congress on Advanced Applied Informatics, vol 81, pages 77-88.

Links:	https://easychair.org/publications/paper/WJH1g
	https://doi.org/10.29007/pn3m

BibTeX entry

@inproceedings{IIAIAAI2021-Winter:Detection_Bottleneck_Manufacturing_Supply,
  author    = {Yoshiatsu Kawabata and Yuta Hosokawa and Katsuhide Fujita},
  title     = {Detection of Bottleneck in Manufacturing Supply Chain using Specific KPI},
  booktitle = {Proceedings of 11th International Congress on Advanced Applied Informatics},
  editor    = {Tokuro Matsuo},
  series    = {EPiC Series in Computing},
  volume    = {81},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/WJH1g},
  doi       = {10.29007/pn3m},
  pages     = {77-88},
  year      = {2022}}

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