Adjust Jidoka Occupational Fatigue Factors to Reduce Idle Times and Defects Using Data Mining (case study) | ||
| The Egyptian International Journal of Engineering Sciences and Technology | ||
| Article 7, Volume 19, EIJEST, Vol. 19, 2016, June 2016, Pages 312-318 PDF (781.94 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/eijest.2016.97147 | ||
| Author | ||
| A Abed* | ||
| Zagazig University, Engineering Faculty, Zagazig , Egypt | ||
| Abstract | ||
| The Jidoka Occupational fatigue represents a major threat for the continuation of the work because generating idle times then defects that disable the productivity for more than 1 day (eg., casual vacation). The main objective of Jidoka is solving of mistakes that occur in a process. When there is an abnormal situation arises the machine, stops and the Labour will stop the production line. Automation (Jidoka) prevents the production of defective products; adjust over-process if necessary and focuses attention on understanding the problem and ensuring that it never recurs. This paper identifies the major factors increasing the risk of a fatal occupational fatigue and idle times in order to provide further evidence for the design and implementation of preventive measures in Jidoka settings. The CAPMAS registered occupational fatigue that causes absence and their characteristics in some industry cities. The fatal occupational fatigue was registered until mid of 2015 (n = 269) were compared to a sample of non-fatal fatigue in same year (n = 1153). Risks of idle-times adjusted by occupational factors significantly associated by logistic regression models. Compared to non-fatal, fatal occupational fatigue mostly produced by natural causes such movable devices|| labourers in narrow area. The fatigue parts of body were a head, terminals, or internal organs. The data-mining analysis showed increased risk of fatality after an idle times for males (adjusted odds ratio = 10.92; 95% Confidence), temporary labourers (5.18; 95%), and the risk increased with age and with advancing hour of the work shift (p for trends <0.01). The main purpose of the paper is to draw attention to join the occupational fatigue to the list of waste, which dealt with Lean. These data help to define priorities for programs that prevent occupational fatigue, idle times and defects. | ||
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