SCRIS: A knowledge-based system tool for assisting manufacturing organizations in identifying supply chain risks

Anish Sachdeva, Vishal Sharma, D. Arvind Bhardwaj, Berman Kayis, Putu Dana Karningsih

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)

Abstract

Risk identification is the first and crucial step in supply chain risk management process. Due to the nature and complexity of supply chain networks of manufacturing organizations, risk identification nowadays has become more challenging. The purpose of this paper to present the development of a tool, called Supply Chain Risk Identification System (SCRIS), for assisting decision makers in identifying existing risks, and the interrelationship of risks in supply chain (SC) network, by considering different process strategies, namely make to stock (MTS), make to order (MTO) and engineering to order (ETO). SCRIS is developed using a knowledge-based system (KBS) approach. The knowledge is represented in ruled based form and written using CLIPS expert system language program. To ensure its feasibility, SCRIS is validated using real case studies in several manufacturing industries. Feedback gathered from organizations involved in validations processes imply the benefit of using SCRIS as a decision support tool in identifying SC risks. SCRIS also has additional positive role in supply chain risk management (SCRM) by promoting communication and collaboration between SC partners. SCRIS provides an extensive tool using KBS approach which covers hundreds of SC risk sub-factors, risk factors, and risk events, as well as mapping the interactions and considering different process strategies which have not been developed to date. A novel SC risks taxonomy is also proposed which encompasses broader issues in the SC network.

Original languageEnglish
Pages (from-to)834-852
Number of pages19
JournalJournal of Manufacturing Technology Management
Volume23
Issue number7
DOIs
Publication statusPublished - 7 Sept 2012
Externally publishedYes

Keywords

  • Deductive databases
  • Knowledge based system
  • Manufacturing industries
  • Risk identification
  • Risk management
  • Supply chain management
  • Supply chain risk management

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