Implementing an integrated maintenance management system for monitoring production lines: a case study for biscuit industry. Issue 1 (13th October 2020)

• Record Type: Journal Article
• Authors: Amrani, Mokhtar Ali; Alhomdi, Mansour; Aswaidy M, Badiea; Ghaleb, Atef M.; Al-Qubati, Mohyeddine; Shameeri, Mutahar
• Is Part Of: Journal of quality in maintenance engineering. Volume 28:Issue 1(2022)
• Page Start: 180
• Page End: 196
• Publication Date: 2020-10-13
• Subjects: Predictive maintenance -- OEE -- Wear debris -- Machine failure -- Oil-based maintenance -- Proactive maintenance; Plant maintenance -- Quality control -- Periodicals; Total quality management -- Periodicals; Total productive maintenance -- Periodicals; 658.202
• DOI: 10.1108/JQME-06-2020-0049
• Languages: English
• ISSNs: 1355-2511

Abstract

Abstract : Purpose: This study provides a unique integrated diagnosis system to investigate the causes of low productivity, profitability, machinery health conditions and wear severity of medium-size biscuit industry assets in Taiz, Yemen. Design/methodology/approach: The evaluation is based on an integrating of the overall equipment effectiveness (OEE) and oil-based maintenance (OBM) approaches. The data are collected using the company's operational records, interviews and observations, while the used lubricating oil samples are also collected from production lines' machineries. Scanning electron microscope (SEM) is used to study the wear debris particle features and wear mechanism. Different other analysis tools such as fishbone, 5 whys and Pareto charts are also used to investigate the root causes and plausible recovery solutions of machinery failures. Findings: This study demonstrated that a large proportion of machinery failures and production loss are of management concerns. Also, this study inferred that the analysis of wear debris is unique and informative for determining machinery wear severity and useful life. Finally, the current conditions of production lines are clarified and suggestions to use a mixed preventive/predictive maintenance management approach are also elucidated. Originality/value: This work implemented an integrated OEE/OBM diagnostic maintenance system to investigate the root causes of low productivity and machine failures in real production lines and suggested robust decisions on the maintenance duties.