Showing papers in "Computers & Industrial Engineering in 2022"

TL;DR: In this paper , the authors present a detailed discussion of the implementation of smart and digital villages with different new digital technologies and also present the possible enhancements in the village with the digitized village concept.

TL;DR: In this article , a new Choquet Integral based interval type-2 trapezoidal fuzzy multiple attribute group decision making (GDM) for sustainable supplier selection (SSS) is proposed.

TL;DR: In this article , a generic framework using Ethereum smart contracts and decentralized storage systems is proposed to automate the processes and information exchange and present detailed algorithms that capture the interactions among supply chain stakeholders.

TL;DR: In this article , a novel MCGDM approach based on intuitionistic fuzzy sets (IFSs) and the VIKOR method for assessing the capacity of CMW recycling channels was presented.

TL;DR: In this article , the authors investigated the role and implications of IDT of I4.0 for the Agile Supply Chain (ASC) strategy through a systematic literature review of 123 identified papers.

TL;DR: In this paper , the authors proposed a systematic literature review investigating and systematizing the knowledge around the circular supply chain domain enabled by Circular Economy (CE) and Industry 4.0 (I4.0) paradigms.

TL;DR: In this paper , the authors examined the impact of big data driven innovation and technology capability of the SME on its supply chain system and investigated the moderating role of SME technology leadership support on SME performance in the post COVID-19 scenario.

TL;DR: Wang et al. as discussed by the authors proposed an integrated decision framework involving Multi-Criteria Decision-making (MCDM)-based Quality Function Deployment (QFD) method with Hesitant Fuzzy Linguistic Term Sets (HFLTS) to investigate the true potential of blockchain to address the circular economy (CE) adoption barriers.

TL;DR: Wang et al. as discussed by the authors developed an optimization model to impute missing elements for an hesitant fuzzy linguistic preference relations (IHFLPR) in group decision making (GDM) problems.

TL;DR: In this article , a cleaner multi-stage production management system for carbon emissions reduction and active participation in corporate social responsibility activities, while also advancing the system economically, is presented, where a planned backorder policy is advised to address anticipated shortages and improve the system's service level.

TL;DR: In this article , an image-based analysis using computational intelligence has proved beneficial in estimation of categorical age in the crops, which can significantly differentiate the wheat crops from the other unwanted plants and weeds while identifying the crop yield age into categorical classes.

TL;DR: In this paper , a green supply chain management with less pollution for biodegradable products is developed and an outsourcing strategy is included only to control the quality of the finished bio-products which would be delivered to the multi-retailer.

TL;DR: In this paper , a smart single-stage production model with an autonomation inspection technology is considered to develop this prevailing study, and the decision-making variables are obtained through a classical optimization technique.

TL;DR: In this paper , a blockchain-based smart contract for supply chain transactions is proposed, which enables decentralized authorization, process automation, and information sharing among the stakeholders in the supply chain stakeholders, and benefits the supplier by lowering the risk of non-payment during the credit period.

TL;DR: In this article , a systematic literature review approach is adopted to systematize such knowledge in a singular and consolidated perspective on Industry 4.0 technologies and work, and the authors show how these technologies create positive and negative impacts on workers.

TL;DR: In this paper , the effectiveness of a variable production system under emissions control policies is observed for a single type of product and a dual-channel policy is utilized to find the most profitable managerial decisions.

TL;DR: In this article , a hybrid self-adaptive multi-objective evolutionary algorithm based on decomposition (HPEA) is proposed to solve the problem of flexible job shop scheduling with fuzzy processing time.

TL;DR: In this article , the authors analyzed the impact of the SARS-CoV-2 pandemic on the workforce and supply resilience in a holistic manner and argued that forward-looking manufacturing companies should turn a disruptive event like a pandemic in an opportunity for digital and technological innovation of the workplace inspired by the principles of harmonic digital innovation (that places the human well-being at the center).

TL;DR: In this article , the authors implemented a UAV network based on IoT (Internet of Things) and a cloud server for the smart city for tracking the air quality of the landfill sites in real-time and alerting the UAV for capturing the visuals from the camera for detecting the exact cause of the pollutant.

TL;DR: Wang et al. as mentioned in this paper established a distributed two-stage reentrant hybrid flow shop bi-level scheduling model, which takes makespan, total carbon emissions and total energy consumption costs as the optimization objectives.

TL;DR: In this article , guidelines for the design of safe human-robot collaborative assembly are developed and classified, particularly focusing on the features characterizing the entire system, and validated by means of a laboratory case study and a digital twin.

TL;DR: In this article , the authors proposed policy recommendations for the electric power industry to realize carbon emissions peaking and carbon neutrality in five scenarios based on the Low Emission Analysis Platform (LEAP) model.

TL;DR: In this paper , the authors formalized a framework that provides guidance on how supplier selection should be formulated and approached for different types of items segmented in Kraljic's portfolio matrix and production policies.

TL;DR: In this paper , the authors presented a modeling and solution approach for a robust job shop scheduling problem under deterministic and stochastic machine unavailability caused by planned preventive maintenance (PM) and unplanned corrective maintenance (CM) following random breakdowns.

TL;DR: In this article , an improved A* algorithm is proposed to solve the robot path planning problem more efficiently and smoothly than the other algorithms mentioned above, and the practicability of the proposed algorithm is validated on the TurtleBot3 Waffle Pi mobile robot.

TL;DR: In this article , a qualitative analysis of in-depth interviews reveals the most important uncertainties and risks (COVID-19 measures, employee welfare, forecast horizon, demand change, and government regulations) and risks for LSPs.

TL;DR: In this article , the authors proposed a new integrated CRITIC-COPRAS method on under interval-valued Fermatean fuzzy numbers to solve multi-criteria decision making (MCDM) problem.

TL;DR: In this paper , a Stackelberg game supply chain consisting of a manufacturer with possible misreport behavior and one retailer with possible fairness concern is investigated, and optimal decisions and profits under different scenarios are solved simultaneously and compared, and find that: Firstly, the manufacturer's misreporting behavior is harmful to the retailer.

TL;DR: In this article , a review of Pareto pruning methods for multi-objective optimization problems is presented, which provides insights into the current trends in the field and offers recommendations on potential research directions.

TL;DR: In this article , the authors proposed an improved learning model to predict the severity of the patients by exploiting a combination of machine learning techniques, which used an adaptive boost algorithm with a decision tree estimator and a new parameter tuning process.