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Module-based Quality System Functionality Evaluation in Production Logistics
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.ORCID iD: 0000-0002-7251-0654
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.ORCID iD: 0000-0002-7550-3134
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.ORCID iD: 0000-0002-0006-283X
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.ORCID iD: 0000-0002-0723-1712
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2016 (English)In: Journal of Industrial Engineering and Management, ISSN 2013-8423, E-ISSN 2013-0953, Vol. 9, no 2, 310-329 p.Article in journal (Refereed) Published
Abstract [en]

Purpose: This paper addresses a comprehensive modeling and functionality evaluation of amodule-based quality system in production logistics at the highest domain abstract level ofbusiness processes.

Design/methodology/approach: All domain quality business processes and quality datatransactions are modeled using BPMN and UML tools and standards at the business process anddata modeling. A modular web-based prototype is developed to evaluate the models addressingthe quality information system functionality requirements and modularity in production logisticsthrough data scenarios and data queries.

Findings: Using the object-oriented technique in design at the highest domain level, theproposed models are subject further development in the lower levels for the implementing case.The models are specifically able to manipulate all quality operations including remedy and controlin a lot-based make-to-order production logistics system as an individual module.

Practical implications: Due to the specification of system as domain design structure, allproposed BPMs, data models, and the actual database prototype are seen referential if not asolution as a practical “to-be” quality business process re-engineering template. 

Originality/value: this paper sets out to provide an explanatory approach using differentpractical technique at modeling steps as well as the prototype implementation.

Place, publisher, year, edition, pages
OmniaScience , 2016. Vol. 9, no 2, 310-329 p.
Keyword [en]
business process, data modelling, production logistics, QIS, UML, BPMN, data query
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Engineering and Management
Identifiers
URN: urn:nbn:se:kth:diva-188862DOI: 10.3926/jiem.1509ISI: 000378499500002OAI: oai:DiVA.org:kth-188862DiVA: diva2:940004
Note

QC 20160726

Available from: 2016-06-20 Created: 2016-06-20 Last updated: 2016-07-26Bibliographically approved

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Publisher's full texthttp://www.jiem.org/index.php/jiem/article/view/1509

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