submit CrossRef Open Access Subscribe New Journal Ideal

Click on image to enlarge

Journal of Industrial Engineering and Management Science

Editors-in-Chief:
Michele Albano, Instituto Superior de Engenharia do Porto, Portugal
Kuinam J. Kim, Kyonggi University, South Korea


ISSN: 2446-1822 (Online Version)
Vol: 2018   Issue: 1

Published In:   January 2018

Publication Frequency: Continuous Article Publication


Search Available Volume and Issue for Journal of Industrial Engineering and Management Science


Energy Saving by Blockchaining Maintenance

Special Issue on "Maintenance Performance Measurement and Management"

doi: https://doi.org/10.13052/jiems2446-1822.2018.004
Michele Albano1, Pankaj Sharma2, Jaime Campos3 and Erkki Jantunen4

1CISTER, ISEP, Polytechnic Institute of Porto, Portugal
2Department of Industrial Systems Engineering and Management, Faculty of Engineering, National University of Singapore, Singapore
3Department of Informatics, Linnaeus University, Sweden
4VTT Technical Research Centre of Finland Ltd, Finland

Abstract: [+]    |    Download File [ 3361KB ]    |   Read Article Online

Abstract: The development and interest in Industry 4.0 together with rapid development of Cyber Physical Systems has created magnificent opportunities to develop maintenance to a totally new level. The Maintenance 4.0 vision considers massive exploitation of information regarding factories and machines to improve maintenance efficiency and efficacy, for example by facilitating logistics of spare parts, but on the other hand this creates other logistics issues on the data itself, which only exacerbate data management issues that emerge when distributed maintenance platforms scale up. In fact, factories can be delocalized with respect to the data centers, where data has to be transferred to be processed. Moreover, any transaction needs communication, be it related to purchase of spare parts, sales contract, and decisions making in general, and it has to be verified by remote parties. Keeping in mind the current average level of Overall Equipment Efficiency (50%) i.e. there is a hidden factory behind every factory, the potential is huge. It is expected that most of this potential can be realised based on the use of the above named technologies, and relying on a new approach called blockchain technology, the latter aimed at facilitating data and transactions management. Blockchain supports logistics by a distributed ledger to record transactions in a verifiable and permanent way, thus removing the need for multiple remote parties to verify and store every transaction made, in agreement with the first “r” of maintenance (reduce, repair, reuse, recycle). Keeping in mind the total industrial influence on the consumption of natural resources, such as energy, the new technology advancements can allow for dramatic savings, and can deliver important contributions to the green economy that Europe aims for. The paper introduces the novel technologies that can support sustainability of manufacturing and industry at large, and proposes an architecture to bind together said technologies to realise the vision of Maintenance 4.0.

Keywords: OEE, Blockchain, CPS, IoT, Maintenance.

Integrated Operational Logistics Network (IOLN) Design (Case Study: Iran Khodro Automotive Co) (Phase I)

doi: https://doi.org/10.13052/jiems2446-1822.2018.003
Mahmood Majd1, Mohammad Reza Motamed2, Mohammad Rouhina3, and Javad Khamisabadi4

1Director of Logistics Engineering, IKCO, Tehran, Iran
2IKCO-Peugeot CEO, Tehran, Iran
3Director of Systems Management, IKCO, Tehran, Iran
4Expert of Logistics Engineering, ISEIKCO, Tehran, Iran
Board Member at Young Scientists Scientific Center & Honorary Prof, Kharkov, Ukraine
Member of Industrial Engineering and Operation Management Society, Washington, USA
Board Member at WASTINC, Las Vegas, Nevada, USA
Board Member at Entrepreneurship Scientific Center, Moscow, Russia
Board Member at Management Scientific Center, WBS Torun University, Poland
Board Member at IAOES, London, UK
Member of Committee at WEASC, Athens, Greece
Board Member at Supply chain management Scientific Center, Sandy Bay, Australia
Board Member at Management Scientific Center, AirLanga University, Indonesia
Faculty of Management, Islamic Azad University, Tehran, Iran

Abstract: [+]    |    Download File [ 519KB ]    |   Read Article Online

Abstract: Logistics Engineering has transcended over the decades into an approach for competitive benefits in organisational performance and logistics efficiency. Most industries are recognising that significant savings are available to companies that are able to ordinate and improve within their logistics operations. Companies today face great challenges because the successful supply of many products and services needs to the effective integration of logistics activities across a prolongation supply chain and an increasing geographical separation. Moreover, logistics integration approach involves both internal integration for an ordinated, unified process as well as relationships to react flexibly, changeability, and responsibility to customer’s demands. In this study, by using of Fuzzy Vikor (F-Vikor), the best combination of RIR was selected and RIR Locating was done. The main aim of this paper is survey and design of the integrated operational logistics network (IOLN) and also, a proposed IOLN to integration of the Iran Khodro Co Supply Network. The results show that the optimal combination of RIR was selected as follows: HUB, CRD and RPP. In addition, the most optimal locations were chosen I each logistics operational zone (LOZ), as follows:
LOZ-2: Shahrud (RPP) and Mayamey (CRD)
C-LOZ (Center and North Section): Garmsar (RPP)
C-LOZ: Robat Karim (HUB)
C-LOZ (Center and South Section): Kashan (RPP)
LOZ-3: Bostanabad (RPP) and Zanjan (CRD)

Keywords: Logistics, Supply Chain, Integrated, Fuzzy Vikor, Network, Iran Khodro Co.

Modeling Operational Risk Using Linear Algebra and Monte Carlo Simulation: Enabling Innovative Service Concepts with Simulated Throughput Computations

doi: https://doi.org/10.13052/jiems2446-1822.2018.002
Larissa Laumann1, Daniel Jaroszewski1, Benedikt Sturm1, Kathrin Rose1, Wolfgang Mergenthaler1 and Gunnar Markert2

1FCE Frankfurt Consulting Engineers GmbH, Bessie Coleman-Strasse 7, 60549 Frankfurt am Main, Germany
2Thyssenkrupp Industrial Solutions, Graf-Galen-Strasse 17, 59269 Beckum, Germany

Abstract: [+]    |    Download File [ 331KB ]    |   Read Article Online

Abstract: Industrial maintenance as a service provided by the plant manufacturer is receiving increasing attention throughout the community of plant operators, notably in the cement and mining industry. The main reason is the fact that manufacturers have the deepest knowledge of their own plants. Furthermore, plant operators do not want to worry about maintenance issues and are rather willing to outsource this task to a service provider. The question then is, at what price the operator and the manufacturer are willing to close a service contract. The service provider must make sure that the price covers his expected cost including an eventual insurance fee against extreme damage and that the risk of outliers can be managed. The operator, in turn, must make sure that the price is covered by his income leaving an appropriate profit. Furthermore, the maintenance service provider can ask an insurance company for protection against very large damages. And finally, the investor, granting a loan to the operator, is interested in his own risk.

Keywords: Reliability Engineering, Engineering Applications of Graph Theory, Monte Carlo Simulation, Matrix Inversion.

A Decision-Making Approach for Supplier Selection in the Presence of Supply Risk

doi: https://doi.org/10.13052/jiems2446-1822.2018.001
Z. Khojasteh-Ghamari and T. Irohara

Faculty of Science and Technology, Sophia University, Tokyo, Japan

Abstract: [+]    |    Download File [ 605KB ]    |   Read Article Online

Abstract: In order to deal with the various kind of risks in a supply chain, we need to have different approaches. In this study, we propose a mathematical programming model to manage the supply risk considering multi layer feature of the supply chain. The aim of this model is managing the supply chain risk by controlling the selection of suppliers. By having this approach, we aim to lower the risk of supplier disruption.We examine various datasets to observe the behaviour of the proposed model in different data sizes through the several steps. Analysing the results of different datasets, we show the trend of objective value by increasing data sizes. Besides, we analyse the increasing ratio of cost within different steps of the model. Finally, we discuss the effect of our proposed approach on the total cost.

Keywords: Supply chain risk, Mathematical programming model, Supplier selection, Multi sourcing.

River Publishers: Journal of Industrial Engineering and Management Science