مقاله انگلیسی رایگان در مورد چرا و چگونه نیاز به ثبت دانش ضمنی در تولید داریم – الزویر ۲۰۱۹
مشخصات مقاله | |
ترجمه عنوان مقاله | چرا و چگونه نیاز به ثبت دانش ضمنی در تولید داریم: مطالعات موردی بازرسی بصری |
عنوان انگلیسی مقاله | How and why we need to capture tacit knowledge in manufacturing: Case studies of visual inspection |
انتشار | مقاله سال ۲۰۱۹ |
تعداد صفحات مقاله انگلیسی | ۹ صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research article) |
مقاله بیس | این مقاله بیس میباشد |
نمایه (index) | scopus – master journals – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
۲٫۴۳۵ در سال ۲۰۱۷ |
شاخص H_index | ۷۶ در سال ۲۰۱۸ |
شاخص SJR | ۱٫۰۷۱ در سال ۲۰۱۸ |
رشته های مرتبط | مهندسی صنایع |
گرایش های مرتبط | تولید صنعتی |
نوع ارائه مقاله |
ژورنال |
مجله / کنفرانس | آرگونومی های کاربردی – Applied Ergonomics |
دانشگاه | Industrial Psychology and Human Factors Group, School of Aerospace, Transport and Manufacturing, Cranfield University, Bedford, MK43 0AL, UK |
کلمات کلیدی | دانش ضمنی، بازرسی بصری، تجزیه و تحلیل وظیفه |
کلمات کلیدی انگلیسی | Tacit knowledge, Visual inspection, Task analysis |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.apergo.2018.07.016 |
کد محصول | E11615 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Outline Highlights Abstract Keywords ۱٫ Introduction ۲٫ Background ۳٫ Method ۴٫ Results ۵٫ Discussion References |
بخشی از متن مقاله: |
Abstract Human visual inspection skills remain superior for ensuring product quality and conformance to standards in the manufacturing industry. However, at present these skills cannot be formally shared with other workers or used to develop and implement new solutions or assistive technologies because they involve a high level of tacit knowledge which only exists in skilled operators’ internal cognitions. Industry needs reliable methods for the capture and analysis of this tacit knowledge so that it can be shared and not lost but also so that it can be best utilised in the transfer of manual work to automated systems and introduction of new technologies and processes. This paper describes two UK manufacturing case studies that applied systematic task analysis methods to capture and scrutinise the tacit knowledge and skills being applied in the visual inspection of aerospace components. Results reveal that the method was effective in eliciting tacit knowledge, and showed that tacit skills are particularly needed when visual inspection standards lack specification or the task requires greater subjective interpretation. The implications of these findings for future research and for developments in the manufacturing industry are discussed. Introduction Visual inspection (VI) is a traditional manual activity that involves careful and critical assessment of an object with reference to a predefined standard (Drury and Watson, 2002; Drury and Dempsey, 2012; See, 2012). In manufacturing, VI is used to identify and diagnose defects, which is essential for ensuring products meet satisfactory quality standards (Garrett et al., 2001). Despite typical error rates of between 20% and 30% (Drury and Fox, 1975), human VI has remained essential in manufacturing because the accuracy and efficiency of human visual acuity has remained superior to the visual inspection capabilities offered by available automated alternatives. Thus, although highly labour-intensive, VI continues to be particularly important in safety critical and high value manufacturing (HVM) processes where the consequences of missed defects are of a higher cost for both human and commercial reasons, e.g. “injury, fatality, loss of expensive equipment, scrapped items, rework, or failure to procure repeat business” (See et al., 2017, p. 262). As visual inspection is highly skilled, best practice knowledge and techniques are valuable, and as it is labour-intensive it is a prime candidate for process improvement/automation to enhance process efficiency in the future. |