University of HormozganInternational Journal of Industrial Engineering and Management Science2409-18715120180601Improve Integration Using Contracts, Case Study: Rail Infrastructure414882115ENAnisur RahmanGriffith School of Engineering, Griffith University GoldGopinath ChattopadhyayFaculty of Science, Engineering and Health CQUniversity AustraliaJournal Article20180124<span>Maintenance contracts have received significant attention in last ten years. It has huge potential to reduce the<br /><span>upfront investments in maintenance infrastructure, specialised maintenance facilities, and risk for owners through<br /><span>expert services provided by the original equipment manufacturers and/ or specialist maintenance providers. There is<br /><span>a growing trend for asset intensive Industries to outsource the maintenance services of their complex and critical<br /><span>asset through maintenance contracts due to economic pressure and technical complexities not within the capability<br /><span>of the owner/ user. One of the complex and critical assets in transport infrastructure is rail. To maintain reliable<br /><span>service through safe and uninterrupted rail operation maintenance contracts are currently being used as a cost<br /><span>effective option. However, there is a need to develop mathematical cost models to build into the contract price. In<br /><span>this paper, a conceptual rail maintenance contract model is proposed for estimating cost of outsourcing maintenance<br /><span>that takes into account cost of maintenance, inspection and risk of accidental failure.</span></span></span></span></span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span>University of HormozganInternational Journal of Industrial Engineering and Management Science2409-18715120180601Presenting A DSS Based Simulation for Maintenance and Vehicles Repair Problem495782116ENArshed MehmoodMechanical Engineering Department UET, Taxila, PakistanMirza JahanzaibCollege of Engineering, Qassim University, Saudi ArabiaJournal Article20190124<span>Maintenance support system is formed by all the needed support resources which are related and coordinated<br /><span>between each other to achieve certain objectives such as operational availability of the supported object during its<br /><span>life cycle. This paper describes the decision support system using simulation in the dynamic environment of vehicles<br /><span>repair and maintenance. The study illustrates a case relevant to repair and maintenance decision support system, in<br /><span>which different feasible scenarios has been modeled and modules developed for the analysis and improvement of the<br /><span>existing system. This is done by process mapping of the existing systems and modeling of the existing system in<br /><span>simulation language. Various feasible alternatives illuminated a pathway to significant improvements in customer<br /><span>service, management of work in process, resource utilization, over time and cycle time. It has been learnt that WIP<br /><span>and overtime are the major impediments in the system affecting the performance of the system which can be<br /><span>controlled by suggesting feasible alternatives.</span></span></span></span></span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span>University of HormozganInternational Journal of Industrial Engineering and Management Science2409-18715120180601Flexibility Challenges in Automotive Assembly, An Approach to Stay Competitive344082117ENBjörn DiffnerDepartment of Management & Engineering Linköping University, LinköpingMats BjörkmanDepartment of Management & Engineering Linköping University, LinköpingKerstin JohansenDepartment of Management & Engineering Linköping University, LinköpingJournal Article20190124<span>The undergoing adaptation of mass customization, alongside the development and demand for new power trains, is challenging the<br /><span>manufacturing system of automotive manufacturers. This, in combination with demands from emerging markets and constantly<br /><span>decreasing product lifecycles, calls for increased flexibility. Based on the research findings, key flexibility types for the automotive<br /><span>industry were identified as Mix, New Product, Modification and Volume flexibility. To achieve these flexibilities, the mixed model<br /><span>assembly, modularity and platform strategies are identified as important factors. A generic BOP as part of the platform strategy is<br /><span>central to enable transferring of production</span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span>University of HormozganInternational Journal of Industrial Engineering and Management Science2409-18715120180601Applying 3D Computer Graphics to Design of Automated Assembly Lines253382118ENMasatoshi KitaokaDepartment of Industrial EngineeringToshio FujitaDepartment of Industrial EngineeringHideki KumagaiDepartment of Industrial EngineeringHitoshi TakedaDepartment of Information Management Bunkyo University, Chigasaki, KanagawaJournal Article20190124<span>This paper proposed the design method for an automated assembly lines, for carrying out basic design using three<br /><span>dimensional computer graphics (3DCG).It also proposes a method for performing kaizen and evaluation of<br /><span>automated systems utilizing hierarchic structure diagrams, state transition diagrams, improved tooling flow<br /><span>diagrams, a method for creating a Ladder Logic Diagram(LLD).Using a time Petri net, analyze the bottleneck<br /><span>process, identify problem points, and propose ideas for kaizen.</span></span></span></span><br /><br class="Apple-interchange-newline" /></span>University of HormozganInternational Journal of Industrial Engineering and Management Science2409-18715120180601A New Bayesian-Based Model to Demand Forecast and Inventory Reduction142082119ENMohammad Anwar RahmanIndustrial Engineering Technology, The University of Southern MississippiBhaba R. SarkerDepartment of Industrial Engineering Louisiana State UniversityJournal Article20190124<span>Natural calamities (e.g., hurricane, excessive ice-fall) may often impede the inventory replenishment during the<br /><span>peak sale season. Due to the extreme situations, sales may not occur and demand may not be recorded. This study<br /><span>focuses on forecasting of intermittent seasonal demand by taking random demand with a proportion of zero values<br /><span>in the peak sale season. Demand pattern for a regular time is identified using the seasonal ARIMA (<span><em>S-ARIMA</em><span>)<br /><span>model. The study proposes a Bayesian procedure to the ARIMA (<span><em>BS-ARIMA</em><span>) model to forecast the peak season<br /><span>demand which uses a dummy variable to account for the past years intermittent demand. To capture uncertainty in<br /><span>the <span><em>B-ARIMA </em><span>model, the non-informative prior distributions are assumed for each parameter. Bayesian updating is<br /><span>performed by Markov Chain Monte Carlo simulation through the Gibbs sampler algorithm. A dynamic<br /><span>programming algorithm under periodic review inventory policy is applied to derive the inventory costs. The model<br /><span>is tested using partial demand of seasonal apparel product in the US during 1996-05, collected from the US Census<br /><span>Bureau. Results showed that, for intermittent seasonal demand forecast, the <span><em>BS-ARIMA </em><span>model performs better and<br /><span>minimizes inventory costs than do <span><em>S-ARIMA </em><span>and modified Holt-Winters exponential smoothing method.</span></span></span></span></span></span></span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span></span></span></span></span></span></span></span></span></span></span>University of HormozganInternational Journal of Industrial Engineering and Management Science2409-18715120180601A Statistical Approach to Determine Efficient Fouling Index202582120ENJunya MiyamotoGraduate School of Science and Technology Nagasaki University, NagasakiKozo NakamuraGraduate School of Science and Technology Nagasaki University, NagasakiTsuyoshi NakamuraGraduate School of Science and Technology Nagasaki University, NagasakiJournal Article20190124<span>Desalination using a reverse osmosis (RO) membrane is a complex process that requires preventive maintenance to control the <span>fouling potential of feed water for long-term successful operation. Fouling is caused by scaling, bacterial growth, or the <span>deposition of suspended or dissolved substances. The widely accepted measure of the fouling potential is the silt density index <span>(SDI). We conducted filtering experiments under diverse conditions to gain new insight into the performance and deficiencies of <span>the SDI from a statistical point of view. Based on the results, we developed a new fouling index that is more reliable and feasible <span>than the SDI.</span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span>University of HormozganInternational Journal of Industrial Engineering and Management Science2409-18715120180601A Conceptual Model For Collaborative Commerce Technologies Adoption81482121ENAlain Y.L ChongDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong KongFelix T.S ChanDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong KongKeng Boon OoiFaculty of Business & Finance, University Tunku Abdul Rahman, Jalan University, Bandar Barat, 31900, Kampar, Perak, MalaysiaJournal Article20190124<span>The principle objective of this research is to develop a conceptual model to study the relationships between<br /><span>collaborative commerce tools adoption, collaborative supply chain implementations, service innovations and the<br /><span>competitive advantages gained by manufacturing companies in Hong Kong/China and Malaysia. One challenge for<br /><span>governments in these countries is to ensure that their manufacturing industry remains competitive globally. This<br /><span>paper presents the first stage of our study which aims to develop a conceptual model which will then be empirically<br /><span>tested to formulate strategies that companies and government in Hong Kong/China and Malaysia can use to improve<br /><span>their competitiveness. This study aims to bridge the gap in the existing studies in innovation and supply chain<br /><span>management by firstly focusing on collaboration in supply chain management, and secondly in the service.</span></span></span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span>University of HormozganInternational Journal of Industrial Engineering and Management Science2409-18715120180601Using Fuzzy Set Theory to Ranking Items Case Study: Bangladeshi Coals586482122ENMuhammad ShamsuzzamanDepartment of Industrial Engineering and Management University of SharjahFikri DweiriDepartment of Industrial Engineering and Management University of SharjahA.M.M. Sharif UllahDepartment of Mechanical Engineering
Kitami Institute of Technology, Kitami, Hokkaido, JapanJournal Article20190124<span>This study develops a computational framework for ranking Bangladeshi coals for industrial use based on fuzzy set<br /><span>theory. The ranking process considers coal quality parameters (known as selection or ranking criteria) such as<br /><span><em>sulphur content (ultimate analysis)</em><span>, <span><em>fixed carbon, volatile matter, moisture content, and ash content (proximate</em><br /><span><em>analysis) </em><span>and <span><em>calorific value</em><span>. The selection criteria are fuzzified according to expert’s opinion and the ranges<br /><span>prescribed in literature. Fuzzy sets are employed to recognize the importance of the selection criteria. Finally,<br /><span>Yager’s fuzzy multi-criteria decision-making approach with <span><em>min-max </em><span>aggregator is employed to get the best-ranked<br /><span>coal. Based on the proposed methodology, a software system is developed to facilitate the decision-making process.</span></span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span></span></span></span></span></span></span></span>University of HormozganInternational Journal of Industrial Engineering and Management Science2409-18715120180601Developing a mathematical model based on compaction reduction to optimize inventory policies in poultry farming577082123ENEbrahim TeimouryAssociate Professor, Iran University of Science and Technology, Tehran, IranMohammadhosein BabaeiPh.D. Candidate, Iran University of Science and TechnologyArmin JabbarzadehAssistant Professor, Iran University of Science and TechnologyJournal Article20190124<strong>Purpose</strong>: One of the major concerns of production managers is to increase profit by increasing production volumes. In most production units, an increase in production volume is achieved by increasing production capacity. However, in the livestock production units, one can adopt a different policy called "compaction reduction". In this approach, given that the capacity of living production units is often in accordance with a standard volume and the living organism occupies less space at the earlier ages, each breeding period can begin with more living units than capacity, and after a given period, some of them can be slaughtered.
<strong>Design/methodology/approach</strong>: This paper presents a mathematical model for optimizing compaction operations in meat poultry production units so that it is possible to calculate the various variables of the compaction process, such as the appropriate slaughter time and the number of breeding chicks over capacity.
Findings: Computational study shows the efficiency of this approach and increase the volume of production and profit compared to the traditional approach and not utilizing compaction.
<strong>Originality/value</strong>: Although livestock supply chain and related problems are one of the most important problems in human life, few researchers have focused on them. In this paper poultry farming is considered as one of the most important livestock inventory and a mathematical model is developed to improve total profit.