چکیده:
هدف از این تحقیق مطالعه تاثیر پیادهسازی تکنیک تجزیه و تحلیل حالات خطا و آثار آن در فرآیند (PFMEA) بر بهبود اثربخشی کلی تجهیزات (OEE) در یک کارخانه تولید قند است. ابتدا میانگین اثربخشی کلی تجهیزات در هشت هفتهی کاری متوالی به عنوان پیش آزمون استخراج گردید. سپس انواع خطاهای بالقوه در فرآیند تولید شناسایی و سه پارامتر شدت خطا، احتمال وقوع خطا و احتمال کشف خطا برای هر حالت خطا بصورت مقیاسهای کلامی و با استفاده از توافق جمعی تعیین گردید و با ضرب مقادیر عددی دفازی شدهی متناظر این سه پارامتر در همدیگر، میزان عدد اولویت هر خطا محاسبه گردید. در مرحلهی بعد بوسیله ماتریس شدت-وقوع و جدول رتبهبندی ریسک، 24 خطای اولویتدار مشخص شد. سپس راهکارهای مناسب برای کاهش اثرات و یا حذف خطاهای اولویتدار تعیین و پیادهسازی اقدامات اصلاحی و مداخلات لازم در طول هشت هفتهی کاری برنامهریزی شد. در مدت اجرای مداخلات و در پایان هر هفته اثربخشی کلی تجهیزات به عنوان پس آزمون محاسبه شد. در پایان رابطهی بین تغییرات عدد اولویت خطا (RPN) و OEE در قالب همبستگی پیرسون مورد مطالعه قرار گرفت.
Extended Abstract Abstract The purpose of this study was to investigate the effect of the implementation of the PFMEA on the improvement of the overall equipment effectiveness (OEE) in a sugar factory. First, the average Overall Equipment Effectiveness in the production process in eight consecutive working weeks was extracted as a pre-test. Then, the types of potential failures in the production process were identified and the three parameters of the severity of the failures, the probability of occurrence of the failures and the probability of failures detection for each failure mode were extracted in linguistic variable and determined by group discussion and by collective agreement and multiplied by corresponding numerical values These three parameters in each other, the number of priority numbers for each failure, was calculated. In the next step, 24 priority failures were identified by the severity-occurrence matrix and risk ranking table. Then, appropriate strategies for reducing the effects or eliminating prioritized failures were identified and implemented, corrective actions and necessary interventions were planned over a period of eight weeks. During the implementation of the interventions and at the end of each week, the Overall Equipment Effectiveness was calculated as a post-test. At the end of the study, the relationship between the risk priority number (RPN) and OEE was studied in the form of the Pearson correlation. Introduction Previous studies have shown that reducing or eliminating of failures, effects on machinery and equipment and increasing their availability, quality and performance will lead to improve the quality and quantity of products and services provided by various organizations (Hassan, Siadat, Dantan, & Martin, 2010; Helvacioglu & Ozen, 2014). Many techniques have been developed to identify, assess and manage the risks involved in various processes. FMEA is one of the most efficient of these techniques (Banduka, Mačužić, Stojkić, Bošnjak, & Peronja, 2016; Cândeaa, Kifor, & Constantinescu, 2014; Elahi, 2018). OEE, on the other hand, is one of the tools used to improve the efficiency of the manufacturing process. This simple and practical tool, identify major and common sources of production related losses and divides them into three main groups to improve equipment efficiency (Ahire & Relkar, 2012). The purpose of this research is to investigate the impact of PFMEA implementation on OEE in a sugar manufacturing company. Case study The research was carried out at the Kurdistan Sugar Factory. Materials and Methods At first, the PFMEA implementation team was formed with the participation of process owners and the then process of sugar production from raw sugar to crop production was thoroughly studied and analyzed. In the next step, as the production processes were extracted, the rate of OEE in the production process was extracted over a period of two months and as one-week intervals as a pre-test. Then, in the next phase of the study, within two working months, a variety of possible errors and failures that had an impact on reducing the quantity and quality of product and process outputs were identified. In the next step, according to the types of failures, the three parameters of severity, occurrence probability and detection probability of each failure by collective agreement were extracted in linguistic scales and then fuzzy risk priority number was calculated. Afterward, by using the severity-occurrence matrix and risk ranking table, failures that were on the priority of needing corrective action were identified. Next, during brainstorming sessions, appropriate solutions were suggested for corrective actions, and these strategies were implemented in priority over eight weeks. In order to ensure the effectiveness of the measures taken, OEE was calculated as a post-test at one-week intervals over two working months. By comparing the post-test results with the pre-test results, the effectiveness of the interventions taken was analyzed. In fact, the innovation aspect of this research compared to the past research is the use of appropriate pre-test and post-test to ensure the effectiveness of interventions taken. Also, at the end of each week, the fuzzy risk priority number for the new situation was extracted from the project implementation team and finally, considering the normality of the parameters of the two tools, the correlation coefficient between RPN and OEE during the eight working weeks were tested. Discussion and Results In this study, the OEE technique was used as pre-test and post-test to ensure the accuracy and effectiveness of the actions and interventions implemented in the framework of PFMEA technique implementation. According to the results of this study, fuzzy PFMEA implementation has increased the overall equipment effectiveness, so it can be said that the implementation of PFMEA with the participation of process owners will improve production status and achieve higher effectiveness. Conclusion In this study, the relationship between risk priority numbers and overall equipment effectiveness was negative. Based on the data gathered, the relationship was defined as follows. According to the above correlation formula, by reducing one RPN unit, the overall equipment effectiveness will increase 0.024 units. In other words, proper implementation of corrective actions will reduce the average risk priority number, and this reduction in RPN will in turn increase the overall equipment effectiveness.
خلاصه ماشینی:
سپس انواع خطاهاي بالقوه در فرآيند توليد شناسايي و سه پارامتر شدت خطا، احتمال وقوع خطا و احتمال کشف خطا براي هر حالت خطا بصورت مقياس هاي کلامي و با استفاده از توافق جمعي تعيين گرديد و با ضرب مقادير عددي دِفازي شده ي متناظر اين سه پارامتر در همديگر، ميزان عدد اولويت هر خطا محاسبه گرديد.
تحقيقات گذشته نشان داده است که کاهش يا حذف حالات و آثار خطا در ماشين آلات و تجهيزات و افزايش سطح دسترسي ، سطح کيفيت و سطح عملکرد آنها موجب ارتقاي کمي و کيفي توليد محصولات و ارائه خدماتِ سازمان - هاي مختلف خواهد شد(٢٠١٠ ,Martin &Hassan, Siadat, Yves Dantan, ).
هدف از 1-Failure Mode and Effect Analysis 2-Overall Equipment Effectiveness اين تحقيق مطالعه تاثير پياده سازي تکنيک تجزيه و تحليل حالات خطا و آثار آن در فرآيند، بر ميزان بهبود اثربخشي کلي تجهيزات ، در يک شرکت صنعتي توليد قند است .
هرچه عدد اولويت خطا به عدد ١٠٠٠ نزديک تر باشد نشان دهنده ريسک بالاتر و مهم تر بودن خطرات و شکست هاي ايجاد شده در فرآيندهاي توليدي و خدماتي است و بايد علت يا علل آن به سرعت توسط تيم FMEA بررسي شود ( ;٢٠١٠ ,Wen &Chang ٢٠١٩ ,Chuang &Huai-Wei Lo, Lioub, Huang, ).
PFMEA-1-1-2 تکنيک تجزيه و تحليل حالات خطا و آثار آن در فرآيند(PFMEA) براي تحليل و ارزيابي شکست هاي بالقوه در فرآيند توليد و مونتاژ کاربرد دارد( & Asan Soyer, 2015; Jahangoshai Rezaee, Yousefi, Valipour, & Mehdi Dehdar, 2018; ٢٠٠٣ ,Stamatis ;٢٠١٦ ,Kjellberg &Lundgren, Hedlind, ).
S. , Singhai, & Shukla, 2012; Kianfar, Najmi, & Ebrahimi, 2004; Reza Abroshan & Hayati, 2017; T.