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Article
Publication date: 30 October 2024

Rouhollah Khakpour, Ahmad Ebrahimi and Seyed-Mohammad Seyed-Hosseini

This paper aims to integrate zero defect manufacturing (ZDM) with process mining (PM) to avoid defect occurrence during production and improve sustainability.

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Abstract

Purpose

This paper aims to integrate zero defect manufacturing (ZDM) with process mining (PM) to avoid defect occurrence during production and improve sustainability.

Design/methodology/approach

The method is developed based on literature review in ZDM and PM. It uses PM for process discovery as an initial strategy in priority to predict-prevent strategies of ZDM.

Findings

It presents the applicability of the proposed approach in observing manufacturing process behavior, identifying dynamic causes of defects during production, predicting the time of defect occurrence and preventing defective products. It also identifies, explains and measures criteria for environmental, social and economic pillars of sustainability affected by defects and presents the impacts of the proposed approach on sustainability improvement.

Originality/value

The extended view of this research, as well as its analytical approach, helps practitioners to develop their ZDM and PM approaches more holistically. The practical application of this research is illustrated through implementing it in a real-life manufacturing case, where the outcomes prove its applicability in avoiding defect occurrence and improving all three pillars of sustainability.

Details

International Journal of Lean Six Sigma, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-4166

Keywords

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Article
Publication date: 19 March 2024

Rouhollah Khakpour, Ahmad Ebrahimi and Seyed-Mohammad Seyed-Hosseini

This paper recommends a method entitled “SMED 4.0” as a development of conventional single minute exchange of die (SMED) to avoid defect occurrence during production and improve…

538

Abstract

Purpose

This paper recommends a method entitled “SMED 4.0” as a development of conventional single minute exchange of die (SMED) to avoid defect occurrence during production and improve sustainability, besides reducing setup time.

Design/methodology/approach

The method builds upon an extensive literature review and in-depth explorative research in SMED and zero defect manufacturing (ZDM). SMED 4.0 incorporates an evolutionary stage that employs predict-prevent strategies using Industry 4.0 technologies including the Internet of Things (IoT) and machine learning (ML) algorithms.

Findings

It presents the applicability of the proposed approach in (1) identifying the triple bottom line (TBL) criteria, which are affected by defects; (2) predicting the time of defect occurrence if any; (3) preventing defective products by performing online setting on machines during production as needed; (4) maintaining the desired quality of the product during the production and (5) improving TBL sustainability in manufacturing processes.

Originality/value

The extended view of SMED 4.0 in this research, as well as its analytical approach, helps practitioners develop their SMED approaches in a more holistic way. The practical application of SMED 4.0 is illustrated by implementing it in a real-life manufacturing case.

Details

Journal of Manufacturing Technology Management, vol. 35 no. 3
Type: Research Article
ISSN: 1741-038X

Keywords

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Article
Publication date: 16 October 2024

Rouhollah Khakpour, Ahmad Ebrahimi and Seyed-Mohammad Seyed-Hosseini

This paper aims to recommend a method entitled “lean process mining (LPM)” for mapping, analyzing and improving the material/information flows in the value stream of manufacturing…

83

Abstract

Purpose

This paper aims to recommend a method entitled “lean process mining (LPM)” for mapping, analyzing and improving the material/information flows in the value stream of manufacturing processes.

Design/methodology/approach

The method is developed based on literature review and in-depth explorative research in value stream mapping and process mining approaches. The proposed LPM framework consists of three phases including as-realized process state, improvement strategies and reengineered process state. Hence, firstly, extracts the as-realized model, measures the identified wastes and identifies the sources of wastes. Secondly, implements prediction-recommendation-prevention strategies. Thirdly, reengineers the process model and measures the improved wastes.

Findings

It presents the applicability of the proposed approach in (1) online observation of manufacturing process behavior and tracing the process deviations dynamically in real time to identify the sources of waste; (2) avoiding defective products occurring during the production and eliminating the relevant derived wastes including wasted material, wasted energy, waste of labor, excess inventory, increased production lead time and wasted operational costs.

Originality/value

The practical application of LPM is illustrated through implementing it in a real-life manufacturing case. The outcomes prove the remarkable applicability of this method in lean manufacturing to avoid waste occurrence in the value stream.

Details

International Journal of Lean Six Sigma, vol. 16 no. 1
Type: Research Article
ISSN: 2040-4166

Keywords

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