{"title":"Improved Lease-oriented opportunistic Maintenance for Two-machine One-buffer System under Product-service Paradigm","authors":"Wenyu Guo, Tangbin Xia, Guojin Si, B. Sun, E. Pan","doi":"10.1109/IEEM.2018.8607598","DOIUrl":"https://doi.org/10.1109/IEEM.2018.8607598","url":null,"abstract":"With the development of the product-service paradigm, a manufacturing system consists of degradation machines and buffers between them begins to be leased in the practical industry. The leasing profit opportunity (LPO) policy is thus extended to optimize preventive maintenance (PM) actions for this type of two-machine one-buffer system. During the LPO procedure, each machine’s PM time point is dynamically scheduled by minimizing the cost rate. Moreover, one machine’s PM can create a maintenance opportunity for the other because of the relationship of the series structure. Taking the buffer level and different kinds of maintenance cost into consideration, the improved LPO policy evaluates the leasing profit savings to decide whether to take the PM opportunity and execute an Early PM for the other machine. The effectiveness of this improved LPO policy is validated through a case study and the comparison with two traditional policies has been provided.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"759 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133970222","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}
Hongying Shan, Yu Yuan, Yanxiang Zhang, Lina Li, Chuang Wang
{"title":"Lean, Simulation and Optimization: The Case of Steering Knuckle Arm Production Line","authors":"Hongying Shan, Yu Yuan, Yanxiang Zhang, Lina Li, Chuang Wang","doi":"10.1109/IEEM.2018.8607821","DOIUrl":"https://doi.org/10.1109/IEEM.2018.8607821","url":null,"abstract":"This paper studies the application of simulation software and integrates system simulation technology and lean theory. Based on the abstract entity of the knuckle arm line, the existing production line simulation model is established by Flexsim simulation software. We use the theory of production line balance to analyze production line through the process–'modeling simulation-improvement and optimization-modeling simulation'. Exerting lean theory, we explore the process which analyzes and solves problems through simulation software. This line is improved by ECRS principle. The results show that the improvement effect is significant. This paper provides method of reference and practical basis for doing the improvement and simulation optimization of production lines.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131870887","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}
{"title":"Assessing the Agility of Teams within Mechatronic Product Development","authors":"L. Becerril, C. Hollauer, U. Lindemann","doi":"10.1109/IEEM.2018.8607700","DOIUrl":"https://doi.org/10.1109/IEEM.2018.8607700","url":null,"abstract":"Although agile development is increasingly being applied outside software development, the methods, tools and techniques are still new to the manufacturing industry. A major barrier is the difficulty to measure the benefits and limitations. Comparing the working practices of a team before and after implementing agile methods would provide some insights into the applicability and usefulness of concrete methods and tools in the context of mechatronic-product development. Nevertheless, existing agility assessment approaches are subjective, software centered, and/or require previous application of agile methods. The goal of this paper is to provide a holistic assessment of a team’s agility independently of the methods, tools and techniques applied. For this purpose, agile, non-agile and hybrid practices provide a frame of reference to characterize how teams work across 12 project processes (e.g. project monitoring) and five levels of agility.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134211072","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}
{"title":"A Local-branching Heuristic for the Best Subset Selection Problem in Linear Regression","authors":"T. Bigler, O. Strub","doi":"10.1109/IEEM.2018.8607366","DOIUrl":"https://doi.org/10.1109/IEEM.2018.8607366","url":null,"abstract":"The best subset selection problem in linear regression consists of selecting a small subset with a given maximum cardinality of a set of features, i.e explanatory variables, to build a linear regression model that is able to explain a given set of observations of a response variable as exactly as possible. The motivation in building linear regression models that include only a small number of features is that these models are easier to interpret. In this paper, we present a heuristic based on the concept of local branching. Such a heuristic repeatedly performs local-search iterations by applying mixed-integer programming. In each local-search iteration, we consider a different randomly selected subset of the features to reduce the required computational time. The results of our computational tests demonstrate that the proposed local-branching heuristic delivers better linear regression models than a pure mixed-integer programming approach within a limited amount of computational time.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134314868","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}
{"title":"Supplier Selection Model Development for Modular Product with Substitutability and Controllable Lead Time","authors":"Y. A. Hidayat, T. Simatupang","doi":"10.1109/IEEM.2018.8607817","DOIUrl":"https://doi.org/10.1109/IEEM.2018.8607817","url":null,"abstract":"Modular product patterns supported by production systems should be able to cope with the high demand for product variations. In the products that have modular patterns, some components of the module compilers with the other module have the same function/use (commonality) and will be able to mutually replace one another (substitutability). On the other hand, changing in the strategic industrial environments have led to the increases of competition, changes in market structure and increases of consumer bargaining power. Changes in consumer needs are then captured by various companies which led to the concept of mass customization. In this paper we aim to develop a mathematical model that can minimize the total inventory cost to select a single supplier and determine the optimum inventory policy considering the nature of commonality and substitutability between components with controllable lead time.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114182558","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}
{"title":"JIS: Pest Population Prognosis with Escalator Boxcar Train","authors":"K. Yeow, Matthias Becker","doi":"10.1109/IEEM.2018.8607724","DOIUrl":"https://doi.org/10.1109/IEEM.2018.8607724","url":null,"abstract":"Pest population prognosis helps the growers in the greenhouse to keep the pest population below the threshold efficiently. INSIM is one of the recognized pest population simulators. However, the implementation of the INSIM simulation faces some difficulties to be executed as a web service. Thus, we propose a Java-based web application using the mathematical model used in INSIM. Additionally to the known model, our implementation is able to give prognosis boundaries based on uncertainty of the temperature development and pest count. The proposed JIS gives lower and upper estimation of the pest population with the mean accuracy of 66.67% against our experimental validation data. Furthermore, the relationship between the area coverage for each yellow sticky trap and its accuracy percentage is investigated.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114688817","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}
{"title":"Performance Assessment of Product Modules Based on Usage Data Collected Through Embedded Sensors","authors":"Hansi Chen, Lei Zhang, Xuening Chu","doi":"10.1109/IEEM.2018.8607589","DOIUrl":"https://doi.org/10.1109/IEEM.2018.8607589","url":null,"abstract":"Customer needs elicitation is critical to the improvement and development of products. Due to the lack of relevant knowledge, some needs are difficult to perceive or express for ordinary customers in the traditional survey- based techniques such as interviews, questionnaires, and online reviews. Recent advances in technologies for information gathering make it possible to monitor and collect the usage data continuously during the product usage stage. In this research, a new approach is developed to assess the performance requirements of smartphones based on analysis of the operating data collected through embedded sensors. In the proposed approach, customers of the same product are first classified into different segments based on their usage patterns. Then, a data-based performance assessment method is developed to assess the performance of the product for each user considering product modules. A case study is presented to demonstrate the effectiveness of the proposed approach.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117099399","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}
{"title":"Analysis and Optimization of Bottlenecks via Simulation","authors":"Jiao Yuan, Runtong Zhang","doi":"10.1109/IEEM.2018.8607413","DOIUrl":"https://doi.org/10.1109/IEEM.2018.8607413","url":null,"abstract":"Manufacturing enterprises in China always have a price advantage of raw material and labor force. Optimization methods are currently widely used in manufacturing system to improve the performance of their production lines and workshops. To maximum the optimization effects, simulation is increasingly applied to the optimization of manufacturing industry. Flexsim can be a useful tool to cope with this optimization made up of several highly discrete events. This article is based on the manufacturing system of company JKL’s cooler. First, this paper introduces and analyzes the company’s manufacturing condition including process flow and its problems in production. Second, the model will be simulated in order to find the weakness and constraints of this system. Third, we introduce a method to identify bottlenecks and offer a framework to solve bottleneck problems. Then, a model based on the statistics and processes is built. In the final section, the results are evaluated and analyzed.The simulation results show that quantity of the products and efficiency of the machines are evidently improved after optimization, which proves that the optimization is effective.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115393805","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}
{"title":"Visualised Decision Support in Industrial Project Monitoring and Control","authors":"Fan Li, F. Vernadat, A. Siadat, Li Zheng","doi":"10.1109/IEEM.2018.8607307","DOIUrl":"https://doi.org/10.1109/IEEM.2018.8607307","url":null,"abstract":"Regarding the changing global competitive environment in industry, companies are forced increasingly to respond to sophisticated and diverse customer demands with efficient decisions support. Therefore, it is necessary to develop a holistic, easy-to-use and efficient performance measurement and management methodology to support sound decision making in industrial project management. For this purpose, a benefit-cost-value-risk based methodology has been developed for comprehensive performance evaluation. Based on the methodology, a visualised approach has been proposed in this paper to further ease performance evaluation and decision support in industrial project monitoring and control.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123313683","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}
{"title":"Process Safety and Performance Improvement in Oil Refineries Through Active Redundancy and Risk Assessment Method - A Case Study","authors":"M. Loganathan, S. Neog, Sunil Rai","doi":"10.1109/IEEM.2018.8607630","DOIUrl":"https://doi.org/10.1109/IEEM.2018.8607630","url":null,"abstract":"Safety and performance improvement of oil refineries are of paramount importance as far as plant throughput is concerned. The refineries do have several critical units, one such unit is Hydrocracker Unit (HCU), which is used in petroleum refineries to produce mainly diesel and other middle distillates. Maintenance of specified temperature of these products is a real challenge as far as the safety is concerned. During high throughput, the cooler used for cooling the outgoing products like diesel becomes ineffective, which results in increased diesel temperature, leading to unsafe condition and reduced performance. The critical parts of the cooler will further worsen the situation. The case study presents the excerpts of process safety and performance improvement of a HCU cooling system by installing an additional cooler as an active redundancy to reduce the diesel outlet temperature. An effective risk assessment method, FMEA (Failure Mode and Effects Analysis) has been carried out to identify the critical units of the cooler unit.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124940180","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}