Pub Date : 2021-12-13DOI: 10.1109/IEEM50564.2021.9673020
Kendrik Yan Hong Lim, Alejandro Seif, Nimish Agarwal, Nam Tuan Le
The recent global pandemic has exposed vulnerabilities in manufacturing and amplified prevailing concerns towards the development of resilient systems from a supply chain (SC) perspective. Industries are often faced with supply and demand-related disruptions, leading to production lines unable to cope with material shortage and demand spikes, resulting in missed opportunities or wastage. As a prevailing technology in the manufacturing domain, Digital twins (DT) has the potential to support SC disruption management with real-time connectivity, simulation, and decision support functionalities. Thus, this paper proposes a DT system designed to mitigate SC-related disruptions, and facilitates end-to-end visibility, process streamlining, and solution generation to meet these challenges. A case study featuring an individualized production shop floor is further explored to validate the effectiveness of this DT system in disruption management within the FMCG domain. This explorative study hopes to align manufacturing resilience concepts with industrial practices to suit today's academic and industrial environment.
{"title":"Digital Twin-enhanced Approach for Supply Chain Disruption Management in Manufacturing Shop Floors","authors":"Kendrik Yan Hong Lim, Alejandro Seif, Nimish Agarwal, Nam Tuan Le","doi":"10.1109/IEEM50564.2021.9673020","DOIUrl":"https://doi.org/10.1109/IEEM50564.2021.9673020","url":null,"abstract":"The recent global pandemic has exposed vulnerabilities in manufacturing and amplified prevailing concerns towards the development of resilient systems from a supply chain (SC) perspective. Industries are often faced with supply and demand-related disruptions, leading to production lines unable to cope with material shortage and demand spikes, resulting in missed opportunities or wastage. As a prevailing technology in the manufacturing domain, Digital twins (DT) has the potential to support SC disruption management with real-time connectivity, simulation, and decision support functionalities. Thus, this paper proposes a DT system designed to mitigate SC-related disruptions, and facilitates end-to-end visibility, process streamlining, and solution generation to meet these challenges. A case study featuring an individualized production shop floor is further explored to validate the effectiveness of this DT system in disruption management within the FMCG domain. This explorative study hopes to align manufacturing resilience concepts with industrial practices to suit today's academic and industrial environment.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"62 1","pages":"848-852"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84965897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-13DOI: 10.1109/IEEM50564.2021.9672959
C. Kwong, S. Mak, Chiho Li
There have been more and more customers and regulatory requirements in the toy industry. Small and medium-sized toy factories in China have been facing challenges to deal with European and US toy safety requirements. How to establish an effective management system to avoid product recalls or penalties becomes an important question, especially to small and medium-sized toy factories with limited resources. After literature review and a pilot study in 4 toy factories, a conceptual framework has been proposed. In January 2020, these 4 factories followed the framework and implemented the toy safety improvement schemes. In January 2021, they were interviewed again about their implementation status. The results showed that their capabilities in responding to European and US toy safety requirements had been lifted. Positive contributions from Toy safety assessment, Industry 4.0, and ISO 37301 (It supersedes ISO 19600:2014) were confirmed among the tactics. This study provides a valuable framework for manufacturers in selecting and implementing toy product safety tactics in responding to European and US requirements.
{"title":"Effectiveness of the Tactics for Small and Medium-sized Toy Factories in China in Dealing with European and US Toy Safety Requirements","authors":"C. Kwong, S. Mak, Chiho Li","doi":"10.1109/IEEM50564.2021.9672959","DOIUrl":"https://doi.org/10.1109/IEEM50564.2021.9672959","url":null,"abstract":"There have been more and more customers and regulatory requirements in the toy industry. Small and medium-sized toy factories in China have been facing challenges to deal with European and US toy safety requirements. How to establish an effective management system to avoid product recalls or penalties becomes an important question, especially to small and medium-sized toy factories with limited resources. After literature review and a pilot study in 4 toy factories, a conceptual framework has been proposed. In January 2020, these 4 factories followed the framework and implemented the toy safety improvement schemes. In January 2021, they were interviewed again about their implementation status. The results showed that their capabilities in responding to European and US toy safety requirements had been lifted. Positive contributions from Toy safety assessment, Industry 4.0, and ISO 37301 (It supersedes ISO 19600:2014) were confirmed among the tactics. This study provides a valuable framework for manufacturers in selecting and implementing toy product safety tactics in responding to European and US requirements.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"11 1","pages":"1179-1183"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85197024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-13DOI: 10.1109/IEEM50564.2021.9673004
W. Mok
This paper presents a logical database design methodology for a MongoDB NoSQL database. Given a query, the design methodology is able to assist database designers to determine the best set of configurations of data, also known elsewhere as scheme trees, in the database such that the retrieval time of the query can be minimal or reduced. The design methodology first models an application of interest with a conceptual model. Based on our previous researches, the design methodology then generates from the conceptual model as few scheme trees as possible, which will eventually be implemented as MongoDB's collections in the database. To illustrate the design methodology, the COVID-19 data set was downloaded as an example application. The design methodology first conceptualized the data set with an Entity-Relationship model. Multiples queries were then devised to access various parts of the date set, whose executions required retrievals of the attribute values of all or some of the entity types and/or the relationship in the ER model. The design methodology then generated the best sets of scheme trees for the queries.
{"title":"A Logical Database Design Methodology for MongoDB NoSQL Databases","authors":"W. Mok","doi":"10.1109/IEEM50564.2021.9673004","DOIUrl":"https://doi.org/10.1109/IEEM50564.2021.9673004","url":null,"abstract":"This paper presents a logical database design methodology for a MongoDB NoSQL database. Given a query, the design methodology is able to assist database designers to determine the best set of configurations of data, also known elsewhere as scheme trees, in the database such that the retrieval time of the query can be minimal or reduced. The design methodology first models an application of interest with a conceptual model. Based on our previous researches, the design methodology then generates from the conceptual model as few scheme trees as possible, which will eventually be implemented as MongoDB's collections in the database. To illustrate the design methodology, the COVID-19 data set was downloaded as an example application. The design methodology first conceptualized the data set with an Entity-Relationship model. Multiples queries were then devised to access various parts of the date set, whose executions required retrievals of the attribute values of all or some of the entity types and/or the relationship in the ER model. The design methodology then generated the best sets of scheme trees for the queries.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"33 1","pages":"1451-1455"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85210533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-13DOI: 10.1109/IEEM50564.2021.9672608
W. Pan, S. Chou
For the process in the clean room, small particles will not only cause environmental pollution, but also lead to the decrease of product yield. Therefore, it is important to clear away the particles from the body before entering the clean room. This paper described an existing approach for automated monitoring cleaning action on real-time camera. The current method of performing action recognition uses 3D convolutional neural network (3DCNN) and real-time object detection which uses You Only Look Once (YOLO) as backbone. To achieve untrimmed standard cleaning action parsing, our research proposes a new approach by combining the two methods with proposed mechanisms. In addition to considering coarse-grained analysis of different actions, this paper also proposed a fine-grained measure of action completion.
对于在洁净室进行的工艺，小颗粒不仅会造成环境污染，还会导致产品收率的降低。因此，在进入洁净室之前，清除体内的颗粒是很重要的。本文介绍了一种利用实时摄像机自动监控清洗动作的方法。目前的动作识别方法采用三维卷积神经网络(3DCNN)和以You Only Look Once (YOLO)为骨干的实时目标检测。为了实现未修剪的标准清理动作解析，我们的研究提出了一种将两种方法与所提出的机制相结合的新方法。除了考虑对不同动作的粗粒度分析外，本文还提出了一种细粒度的动作完成度量。
{"title":"Untrimmed Operator Standard Cleaning Action Parsing Based on Deep Learning Method","authors":"W. Pan, S. Chou","doi":"10.1109/IEEM50564.2021.9672608","DOIUrl":"https://doi.org/10.1109/IEEM50564.2021.9672608","url":null,"abstract":"For the process in the clean room, small particles will not only cause environmental pollution, but also lead to the decrease of product yield. Therefore, it is important to clear away the particles from the body before entering the clean room. This paper described an existing approach for automated monitoring cleaning action on real-time camera. The current method of performing action recognition uses 3D convolutional neural network (3DCNN) and real-time object detection which uses You Only Look Once (YOLO) as backbone. To achieve untrimmed standard cleaning action parsing, our research proposes a new approach by combining the two methods with proposed mechanisms. In addition to considering coarse-grained analysis of different actions, this paper also proposed a fine-grained measure of action completion.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"2 1","pages":"1338-1342"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85249424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-13DOI: 10.1109/IEEM50564.2021.9672815
Jonny
In today's highly competitive industry, achieving highest Process Cycle Efficiency (PCE) is a must for any company to gain competitive advantage including ABC company. This company has implemented Lean Production throughout the company's manufacturing facilities. In this initiative, a research is conducted using Value Stream Mapping (VSM) to follow all processes used by producing product A as one of the company's line of products. Through this tool, waste was able to be carefully identified and eliminated to gain low-cost product. By doing this, PCE of the company experienced an 56% increase from 15.60% to 29.60% and 44% pricing index. Thus, the implementation of this initiative has given insight that low-cost product can also be gained by improving PCE.
{"title":"Implementation of Lean Production for Achieving Low-cost Product: A Case Study of ABC Company","authors":"Jonny","doi":"10.1109/IEEM50564.2021.9672815","DOIUrl":"https://doi.org/10.1109/IEEM50564.2021.9672815","url":null,"abstract":"In today's highly competitive industry, achieving highest Process Cycle Efficiency (PCE) is a must for any company to gain competitive advantage including ABC company. This company has implemented Lean Production throughout the company's manufacturing facilities. In this initiative, a research is conducted using Value Stream Mapping (VSM) to follow all processes used by producing product A as one of the company's line of products. Through this tool, waste was able to be carefully identified and eliminated to gain low-cost product. By doing this, PCE of the company experienced an 56% increase from 15.60% to 29.60% and 44% pricing index. Thus, the implementation of this initiative has given insight that low-cost product can also be gained by improving PCE.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"29 1","pages":"729-733"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84063854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-13DOI: 10.1109/IEEM50564.2021.9673066
Jonny, Kriswanto, Matsumura Toshio
With the existence of Internet of Things that have ability to connect various devices through censors, the growth of data volume is increasing rapidly known as Big Data. Through this Big Data, many companies gained its insights as basis for better decision making to gain competitive advantage. However, past literatures have shown that these empirical results are still fragmented. Therefore, this paper aims to propose a model on how IoT Big Data impacts business performance. For modeling purposes, some elements are included such as: 1) Business Process Improvement, 2) Marketing Strategies, 3) Business Management Innovation, 4) Business Models and Organizational Culture, 5) Privacy and Ethics, 6) Business Performance. Furthermore, sampling of managers in manufacturing industry are gained to answer several questions regarding the model development. For analysis purposes, Smart PLS 3.0 is run to evaluate the fitness of the model with requirement of Goodness of Fit (GoF) above 0.38. After careful conduct, the model is robust and accurate. From this model it can be said that 1) Business Models & Organizational Culture positively influence Business Process Improvement while Privacy and Ethics negatively influence it, 2) Business Process Improvement positively influences Marketing Strategies, Business Management Innovation and Business Performance, and 3) both Marketing Strategies and Business Management Innovation positively influence Business Performance.
{"title":"Modeling IoT and Big Data Impacts to Business Performance","authors":"Jonny, Kriswanto, Matsumura Toshio","doi":"10.1109/IEEM50564.2021.9673066","DOIUrl":"https://doi.org/10.1109/IEEM50564.2021.9673066","url":null,"abstract":"With the existence of Internet of Things that have ability to connect various devices through censors, the growth of data volume is increasing rapidly known as Big Data. Through this Big Data, many companies gained its insights as basis for better decision making to gain competitive advantage. However, past literatures have shown that these empirical results are still fragmented. Therefore, this paper aims to propose a model on how IoT Big Data impacts business performance. For modeling purposes, some elements are included such as: 1) Business Process Improvement, 2) Marketing Strategies, 3) Business Management Innovation, 4) Business Models and Organizational Culture, 5) Privacy and Ethics, 6) Business Performance. Furthermore, sampling of managers in manufacturing industry are gained to answer several questions regarding the model development. For analysis purposes, Smart PLS 3.0 is run to evaluate the fitness of the model with requirement of Goodness of Fit (GoF) above 0.38. After careful conduct, the model is robust and accurate. From this model it can be said that 1) Business Models & Organizational Culture positively influence Business Process Improvement while Privacy and Ethics negatively influence it, 2) Business Process Improvement positively influences Marketing Strategies, Business Management Innovation and Business Performance, and 3) both Marketing Strategies and Business Management Innovation positively influence Business Performance.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"155 1","pages":"1127-1131"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85393847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-13DOI: 10.1109/IEEM50564.2021.9672859
I. M. Teixeira, A. P. Barroso, T. Marques
In a deregulated electricity market, market participants define trading strategies and models to assist the decision-making process. Companies whose operation is heavily dependent on this market are increasingly adopting electricity price forecasting models to identify sales and purchase contracts with the best price. This paper intends to contribute to the improvement of the decision-making process for purchasing electricity in the Iberian Electricity Market. The purpose is to develop a forecasting model for electricity spot prices based on prices established on the derivatives markets. The model uses Artificial Neural Networks trained with the Extreme Learning Machine algorithm to determine the monthly average spot prices for the next six months and provides a tool for making trading decisions considering the risk of exposure to spot market volatility. The forecasting model was applied in two scenarios: pre-pandemic and pandemic. The results prove that its application can contribute to improving decision-making for trading electricity in the short/medium term. Experimental results considering both scenarios show that the proposed model can provide month-ahead forecasts with an RMSE up to 6.38 €/MWh.
{"title":"Extreme Learning Machine for Short and Mid-term Electricity Spot Prices Forecasting","authors":"I. M. Teixeira, A. P. Barroso, T. Marques","doi":"10.1109/IEEM50564.2021.9672859","DOIUrl":"https://doi.org/10.1109/IEEM50564.2021.9672859","url":null,"abstract":"In a deregulated electricity market, market participants define trading strategies and models to assist the decision-making process. Companies whose operation is heavily dependent on this market are increasingly adopting electricity price forecasting models to identify sales and purchase contracts with the best price. This paper intends to contribute to the improvement of the decision-making process for purchasing electricity in the Iberian Electricity Market. The purpose is to develop a forecasting model for electricity spot prices based on prices established on the derivatives markets. The model uses Artificial Neural Networks trained with the Extreme Learning Machine algorithm to determine the monthly average spot prices for the next six months and provides a tool for making trading decisions considering the risk of exposure to spot market volatility. The forecasting model was applied in two scenarios: pre-pandemic and pandemic. The results prove that its application can contribute to improving decision-making for trading electricity in the short/medium term. Experimental results considering both scenarios show that the proposed model can provide month-ahead forecasts with an RMSE up to 6.38 €/MWh.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"73 1","pages":"452-456"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87998607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-13DOI: 10.1109/IEEM50564.2021.9672884
Junyi Chai, Wenbin Liu
Multicriteria ranking has been the center of Multicriteria decision making (MCDM) for a long time, which usually assumes a simple structure of criteria and the objective values of evaluations. In this study, we develop a new multicriteria ranking approach that considers people's subjective attitudes on objective rankings and accommodates a hierarchical structure of criteria. Our new approach, called weighted subjective skyline ranking (WSSR), can capture people's tastes (or bias) under a hierarchy of multicriteria. As a unique behavioral feature, this WSSR accounts for the diminishing sensitivity of people. We can quantitatively characterize the influence of people's subjective attitudes in processing multicriteria ranking. We consider the world university ranking as a practical scenario of implementation through this study. Interestingly, using the WSSR uncovers essentials and bias in prevailing world university ranking systems. This study provides a deeper understanding of the influence of the human factor on multicriteria ranking.
{"title":"A Weighted Subjective Skyline Approach for World University Ranking Systems","authors":"Junyi Chai, Wenbin Liu","doi":"10.1109/IEEM50564.2021.9672884","DOIUrl":"https://doi.org/10.1109/IEEM50564.2021.9672884","url":null,"abstract":"Multicriteria ranking has been the center of Multicriteria decision making (MCDM) for a long time, which usually assumes a simple structure of criteria and the objective values of evaluations. In this study, we develop a new multicriteria ranking approach that considers people's subjective attitudes on objective rankings and accommodates a hierarchical structure of criteria. Our new approach, called weighted subjective skyline ranking (WSSR), can capture people's tastes (or bias) under a hierarchy of multicriteria. As a unique behavioral feature, this WSSR accounts for the diminishing sensitivity of people. We can quantitatively characterize the influence of people's subjective attitudes in processing multicriteria ranking. We consider the world university ranking as a practical scenario of implementation through this study. Interestingly, using the WSSR uncovers essentials and bias in prevailing world university ranking systems. This study provides a deeper understanding of the influence of the human factor on multicriteria ranking.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"82 1","pages":"383-387"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90882269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-13DOI: 10.1109/IEEM50564.2021.9672960
D. Nguyen
The appearance of layering manufacturing technologies as called 3D printing or additive manufacturing changed the way we design and fabricate the product. The more complex geometric surfaces of the product are able to be manufactured thanks to these technologies. However, these technologies still have several technological limitations such as materials, thermal deformation, removal of support structures, etc., and they have a strong influence on the manufacturability of the technology. Therefore, a new approach is presented in the paper that allows us to analyze the manufacturability for additive manufacturing based on the global performance index. The index is defined to evaluate the appropriateness of an additive manufacturing technology that we used to fabricate the designed product.
{"title":"An Appropriateness Analysis for Additive Manufacturing Based on a Global Performance Index","authors":"D. Nguyen","doi":"10.1109/IEEM50564.2021.9672960","DOIUrl":"https://doi.org/10.1109/IEEM50564.2021.9672960","url":null,"abstract":"The appearance of layering manufacturing technologies as called 3D printing or additive manufacturing changed the way we design and fabricate the product. The more complex geometric surfaces of the product are able to be manufactured thanks to these technologies. However, these technologies still have several technological limitations such as materials, thermal deformation, removal of support structures, etc., and they have a strong influence on the manufacturability of the technology. Therefore, a new approach is presented in the paper that allows us to analyze the manufacturability for additive manufacturing based on the global performance index. The index is defined to evaluate the appropriateness of an additive manufacturing technology that we used to fabricate the designed product.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"31 2 1","pages":"634-638"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82751574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-13DOI: 10.1109/IEEM50564.2021.9672777
M. Kratzer, L. Bauch, T. Burkert, B. Szost, T. Bauernhansl
Engineering Changes (ECs) cause significant effort in the automotive industry. With increasing complexity and functionalities of vehicles on the one hand, and decreasing time to market on the other hand, managing ECs becomes more crucial. Especially ECs affecting part-specific tools consume much time and costs in the development of an automobile. To find strategies for reducing this effort, it is important to understand when and why ECs occur. Therefore, this paper first investigates the distribution over time of 3561 EC Orders (ECOs) of three vehicle development projects. A similar pattern with peaks after hardware development phases is observed. Second, the ECOs are categorized according to their reasons. The most frequent reasons are assembly problems, design, and geometric conflicts. Third, the share of reasons over time is analyzed. Whereas some reasons like cost reduction occur early in the development process, others like assembly problems or acoustics appear later. The authors suggest that some ECs with reasons like acoustics should be either done earlier or reduced e.g. through increased virtual validation whereas others with reasons like design should be done more efficiently.
{"title":"Reasons for Engineering Changes Affecting Part-specific Tools: An Investigation in the Automotive Industry","authors":"M. Kratzer, L. Bauch, T. Burkert, B. Szost, T. Bauernhansl","doi":"10.1109/IEEM50564.2021.9672777","DOIUrl":"https://doi.org/10.1109/IEEM50564.2021.9672777","url":null,"abstract":"Engineering Changes (ECs) cause significant effort in the automotive industry. With increasing complexity and functionalities of vehicles on the one hand, and decreasing time to market on the other hand, managing ECs becomes more crucial. Especially ECs affecting part-specific tools consume much time and costs in the development of an automobile. To find strategies for reducing this effort, it is important to understand when and why ECs occur. Therefore, this paper first investigates the distribution over time of 3561 EC Orders (ECOs) of three vehicle development projects. A similar pattern with peaks after hardware development phases is observed. Second, the ECOs are categorized according to their reasons. The most frequent reasons are assembly problems, design, and geometric conflicts. Third, the share of reasons over time is analyzed. Whereas some reasons like cost reduction occur early in the development process, others like assembly problems or acoustics appear later. The authors suggest that some ECs with reasons like acoustics should be either done earlier or reduced e.g. through increased virtual validation whereas others with reasons like design should be done more efficiently.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"7 1","pages":"477-481"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84191523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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