Showing papers in "Computers & Industrial Engineering in 2019"

TL;DR: A systematic literature review of ML methods applied to PdM, showing which are being explored in this field and the performance of the current state-of-the-art ML techniques.

TL;DR: In this article, a comprehensive study on various factors, that affects the sustainable supply chain were analyzed and the results recorded, based on the review, a framework for assessing the readiness of supply chain organization from various perspectives has been proposed to meet the requirements of the fourth Industrial Revolution.

TL;DR: In this survey, fourteen new and outstanding metaheuristics that have been introduced for the last twenty years other than the classical ones such as genetic, particle swarm, and tabu search are distinguished.

TL;DR: How the blockchain can be integrated into the supply chain architecture to create a reliable, transparent, authentic and secure system is described.

TL;DR: A reference architecture of the blockchain-based logistics monitoring system (BLMS) was programmed and tested based on Ethereum and demonstrates how blockchain can be implemented in the operations and supply chain context by using software components.

TL;DR: A software connector has been designed and developed to connect an Ethereum-like blockchain with the enterprises’ information systems to allow companies to share information with their partners with different levels of visibility and to check data authenticity, integrity and invariability over time through the blockchain, thus building trust.

TL;DR: A mixed integer programming (MIP) formulation is presented that captures the delivery concept of a truck-drone combination along with the idea of allowing autonomous drones to fly from delivery trucks, make deliveries, and fly to any available delivery truck nearby.

TL;DR: A systematic literature review is presented, consisting of quantitative and qualitative data, focusing on investigating to what extent, what type, and how academic publications on Industry 4.0 integrate human factors and ergonomics in their research.

TL;DR: Key aspects related to architectural design, entity relations, interactions among participants, information flow, implementation and testing of the overall system functionality with a potential business case applied to vaccine supply chain are presented.

TL;DR: A multi-criteria decision making (MCDM) based framework is proposed that is used to evaluate green supplier selection by using an integrated fuzzy Analytical Hierarchy Process (AHP) with the other three techniques namely MABAC (“Multi-Attributive Border Approximation Area Comparison”), WASPAS (”Weighted Aggregated Sum-Product Assessment”) and TOPSIS ( “Technique for order preference by similarity to ideal Solution

TL;DR: A framework for investigating barriers to the adoption and successful implementation of blockchains across different industries and services is developed, using DEMATEL technique, and finds that challenges in scalability and market-based risks are the most influencing barriers.

TL;DR: This research supports academics and practitioners in effectively adopting MCDM methods to overcome the deficiencies of the traditional FMEA and provides an insight into its state-of-the-art.

TL;DR: The results showed that human and technological factors are the most important factors for medical tourism adoption in Malaysia.

TL;DR: A new integrated interval rough number (IRN) approach based on the Best Worst Method (BWM) and Weighted Aggregated Sum Product Assessment (WASPAS) method along Multi-Attributive Border Approximation area Comparison (MABAC) to evaluate 3PL providers is presented.

TL;DR: A Multi-Agent Systems approach is proposed for addressing sustainable supplier evaluation and selection process to provide a proper communication channel, structured information exchange and visibility among suppliers and manufacturers and it is found that the proposed approach can help decision-makers inside manufacturing firms to make prompt decisions with less human interactions.

TL;DR: Results show that isolated production and distribution network design optimisation can lead to severe decreases in performance in the event of SC disruptions, and contingency recovery policies need to be applied during the disruption period along with a revival policy in the post-disruption period to avoid disruption tails.

TL;DR: A hybrid task scheduling algorithm named FMPSO that is based on Fuzzy system and Modified Particle Swarm Optimization technique to enhance load balancing and cloud throughput and achieves the goal of minimizing the execution time and resource usage is proposed.

TL;DR: Results reveal that increased market scale caused by a disruption, lower greening cost and lower level of customers' loyalty to the retail channel are not only beneficial for the supply chain, but also bring more enhancements to the greening level of green products.

TL;DR: This research explores the existing body of knowledge by examining the critical barriers to the adoption of BDA in manufacturing supply chains in the context of Bangladesh using a Delphi-based analytic hierarchy process (AHP).

TL;DR: An effective comprehensive framework is proposed to evaluate and select the optimal EVCS site under picture fuzzy environment and results indicate that the proposed framework is useful for identifying suitable EV CS site among the potential charging stations.

TL;DR: An improved discrete grey multivariable model is designed to forecast the future output value of the high-tech industries that cover large and medium-sized enterprises in China’s eastern region and outperforms a range of benchmark models.

TL;DR: Evidence of a positive relationship between the adoption of Cloud Computing use in process/activity integration, technology/system integration, and supply chain partner integration is provided and it is indicated that Cloud computing use in supply chain can also have an impact on the integration of the supply chain’s information, physical and/or financial flows.

TL;DR: A new method called R-TOPSIS is put forward, which proved to be robust in the experiments performed, since there were no cases of rank reversal for either the simulated cases nor for the real case used to validate it.

TL;DR: A novel model is developed that summarizes the main capabilities of BDA in the context of manufacturing process and will help companies to understand the big data analytics capabilities and its potential implications for their manufacturing processes and support them seeking to design more effective BDA-enabler infrastructure.

TL;DR: A new object detection framework, classification priority network (CPN), and a new classification network, multi-group convolutional neural network (MG-CNN), to inspect the defects of steel surface to improve the accuracy of defect inspection.

TL;DR: A systematic literature review on the applications of learning curves in production and operations management is presented, with a framework that includes typical learning curve models developed and a discussion of the most important and informative articles in each of the major categories.

TL;DR: This work proposes two novel methodologies to solve MADM problems with evaluation of fuzzy information, which rely on novel and flexible fuzzy rough set models and observes that the optimal selected alternative is the same, which means that these two decision-making methods are reasonable.

TL;DR: Research findings proved that the developed GR-FMOPM could be used as a tool in evaluating and ranking related facilities with respect to their resilience performance and a trade-off among economic, green and resilience objectives.

TL;DR: The proposed comprehensive estimation method resembles the Bayesian approach, and consequently it can enhance the reliability for the evaluation of the incomplete elements in GDM and a consensus reaching process for GDM with incomplete preference information is proposed.

TL;DR: An inclusive multi-objective mixed integer linear programming model is developed, which accounts for multiple periods, multiple products and multimodal transportation, to evaluate suppliers and allocate order quantities and the preferable solution is intelligently selected based on the DEA super efficiency score of all purchasing firms as a decision support tool.