Article
Computer Science, Interdisciplinary Applications
Dimitris Mourtzis, John Angelopoulos, Vasilios Zogopoulos
Summary: The importance of interconnecting multiple digital systems through digitalization of manufacturing systems is highlighted. Internet and Communication technologies enable the connection of shop-floor technicians with machine sensors data, and mobile devices with Augmented Reality technology can be used for monitoring and maintenance purposes.
COMPUTERS IN INDUSTRY
(2021)
Article
Computer Science, Interdisciplinary Applications
Yumin Ma, Shengyi Li, Fei Qiao, Xiaoyu Lu, Juan Liu
Summary: This paper presents a data-driven scheduling knowledge life-cycle management method for smart shop floors. The method includes four phases: knowledge generation, knowledge application, online knowledge evaluation, and knowledge update. It uses extreme learning machine and quality control theory to learn, evaluate, and update scheduling knowledge. Experimental results show that the proposed method improves the effectiveness of scheduling knowledge and optimizes the performance of smart shop floors.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2022)
Article
Computer Science, Interdisciplinary Applications
Mageed Ghaleb, Sharareh Taghipour
Summary: This paper addresses the problem of dynamic shop-floor scheduling using real-time information in a case study from the thermoplastic industry. It proposes a predictive-reactive scheduling approach based on a modified simulated annealing (SA) algorithm to generate better real-life planning and scheduling results compared to the methods based on dispatching rules.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Engineering, Industrial
Roberto Cigolini, Simone Franceschetto, Andrea Sianesi
Summary: This paper introduces a new approach to design shop floor control techniques for wafer fabs in the integrated circuit manufacturing industry. Results suggest that the performance of batch work centers can significantly affect the overall fab performance, and improvements can be obtained at the shop floor level via slack-based dispatching procedures.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Yumin Ma, Jingwen Cai, Shengyi Li, Juan Liu, Jianmin Xing, Fei Qiao
Summary: This paper proposes a self-adaptive scheduling approach based on double deep Q-network (DDQN) to reduce manual supervision and improve the effectiveness of self-adaptive scheduling. The approach utilizes reinforcement learning and a dynamic reward function to generate the scheduling model without manual supervision. Experimental results demonstrate the effectiveness of the proposed approach in reducing time and labor costs in dynamic production environments.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Jingru Chang, Dong Yu, Zheng Zhou, Wuwei He, Lipeng Zhang
Summary: With the development of intelligent manufacturing, machine tools play a crucial role in the equipment manufacturing industry. This paper proposes a hierarchical reinforcement learning algorithm to solve the multi-objective dynamic flexible job shop scheduling problem. Experimental results show that the algorithm outperforms others in terms of solution quality and generalization, and it has the advantage of real-time characteristics.
Article
Computer Science, Artificial Intelligence
Zhen Wang, Qianwang Deng, Like Zhang, Haiqiu Li, Fengyuan Li
Summary: This paper proposes a collaborative optimization problem of spare parts production and worker arrangement driven by O&M. An improved Non-dominated Sorting Genetic Algorithm-II (INSGA-II) is used to solve the mixed integer programming model, which considers the production of spare parts and the limited number of workers. Extensive experiments validate the effectiveness of INSGA-II.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Manufacturing
Xiao Chang, Xiaoliang Jia, Shifeng Fu, Hao Hu, Kuo Liu
Summary: This study proposes an overall framework of DT enabled real-time scheduling for complex product shop-floor. By formulating the scheduling problem as Markov Decision Process (MDP) and using deep Q-network (DQN) to achieve optimal task dispatching, it can effectively reduce dynamic disturbances and minimize makespan.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2023)
Article
Computer Science, Interdisciplinary Applications
Feifeng Zheng, Yaxin Pang, Yinfeng Xu
Summary: This work focuses on the problem of cross-docking truck scheduling, considering internal operations and proposing two efficient heuristic algorithms to address the problem.
JOURNAL OF COMBINATORIAL OPTIMIZATION
(2022)
Article
Engineering, Multidisciplinary
Linshan Ding, Zailin Guan, Zhengmin Zhang, Weikang Fang, Zhipeng Chen, Lei Yue
Summary: This article studies a large-scale multiplicity flexible job-shop scheduling problem (FJSP) with sequence-dependent set-up time. A hybrid fluid master-apprentice evolutionary algorithm (HFMAE) is proposed to minimize the makespan. The algorithm utilizes a fluid relaxation initialization method and an improved master-apprentice evolutionary method, along with neighbourhood structures and makespan estimation approaches, to accelerate the solution space search efficiency. Numerical results demonstrate that HFMAE outperforms comparison algorithms in solving large-scale multiplicity FJSPs.
ENGINEERING OPTIMIZATION
(2022)
Article
Computer Science, Interdisciplinary Applications
Yakov Zinder, Alexandr Kononov, Joey Fung
Summary: The paper explores the two-machine scheduling problem where each job is processed on a first-stage machine before moving to a second-stage machine. Jobs require storage space and the goal is to minimize completion time. Instances are classified through five parameters, resulting in 64 families, with computational complexity and polynomial-time solvability established for each family.
JOURNAL OF COMBINATORIAL OPTIMIZATION
(2021)
Article
Computer Science, Information Systems
Ying Liu, Kwan-Wu Chin, Changlin Yang
Summary: This article studies data collection in a multihop IoT wireless network and proposes an algorithm to maximize the amount of data collected by optimizing the sampling and transmission time of tags. The algorithm collects 85% of the optimal amount of samples.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Industrial
Mingze Yuan, Lin Ma, Ting Qu, Matthias Thuerer
Summary: This study focuses on the transient status of urgent operations in the context of workload control (WLC) at the shop floor dispatching stage. It reevaluates the urgency of jobs at the input buffer of each workstation and shows that considering the transient status of urgent operations contributes to speeding up production and improving delivery performance.
IET COLLABORATIVE INTELLIGENT MANUFACTURING
(2023)
Proceedings Paper
Engineering, Industrial
Xiaozheng Xiong, Wenjun Xu, Jiayi Liu, Yang Hu
Summary: This study proposes a collaborative scheduling mechanism for production and transportation based on digital twin. By using a collaborative scheduling model and an improved genetic algorithm, the goal of reducing transportation time in a flexible job shop manufacturing setting is achieved. The experimental results demonstrate the effectiveness of the collaborative scheduling strategy and the superiority of dynamic collaborative scheduling within the digital twin framework.
2022 IEEE 17TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA)
(2022)
Article
Management
Paulo Eduardo Pissardini, Melyssa Albino de Oliveira Bueno, Kayke Hernandes Alves, Luiz Gustavo Mamede Monte
Summary: The advent of Information and Communication Technology has advanced the field of Operations Management, particularly in the application of RFID technology as an Ordering Coordination System. Through a systematic literature review, this study identified the benefits of RFID technology in the implementation of SFC 4.0, and developed an information flow framework. However, the current research is still in its initial stage, and further investigation is needed in the future.
RISUS-JOURNAL ON INNOVATION AND SUSTAINABILITY
(2022)
Article
Engineering, Industrial
Kurt Hozak, James A. Hill
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2010)
Article
Management
James A. Hill, Stephanie Eckerd, Darryl Wilson, Bertie Greer
JOURNAL OF OPERATIONS MANAGEMENT
(2009)
Article
Management
Stephanie Eckerd, James Hill, Kenneth K. Boyer, Karen Donohue, Peter T. Ward
JOURNAL OF OPERATIONS MANAGEMENT
(2013)
Article
Engineering, Manufacturing
Gokce Esenduran, James A. Hill, In Joon Noh
PRODUCTION AND OPERATIONS MANAGEMENT
(2020)
Article
Management
Keith Skowronski, W. C. Benton, James A. Hill
JOURNAL OF OPERATIONS MANAGEMENT
(2020)
Article
Engineering, Manufacturing
Mengyang Pan, Aravind Chandrasekaran, James Hill, Manus Rungtusanatham
Summary: R&D projects in small biotechnology firms often involve knowledge from multiple technical fields and research in different problem domains. Resource-constrained small firms face challenges when the project knowledge scope increases. The principal investigators (PIs) play a crucial role in managing project ideas and promoting learning across projects. This research explores how small firms' PIs manage projects with high knowledge scope and finds a negative association between project knowledge scope and project success, which is amplified by the multiproject status of PIs and weakened by project management experience. The shared problem domain is identified as a key contingency for these moderation effects.
PRODUCTION AND OPERATIONS MANAGEMENT
(2022)
Article
Business
Mengyang Pan, James Hill, Ian Blount, Manus Rungtusanatham
Summary: Historically, minority businesses in the U.S. have faced growth barriers in mainstream markets. Institutional intermediaries have emerged as a low-cost solution, helping these businesses access corporate members and providing training to improve their management skills. A study on minority businesses affiliated with NMSDC regional council found that their participation in intermediary-sponsored activities influences their relationships with corporate and minority members. Government contracting experience strengthens the impact of relationship building on growth. African American minority businesses experience higher growth from building relationships with other minority members compared to Hispanic and Asian minority businesses.
JOURNAL OF BUSINESS RESEARCH
(2022)
Article
Management
Stephanie Eckerd, Kenneth K. Boyer, Yinan Qi, Adam Eckerd, James A. Hill
JOURNAL OF SUPPLY CHAIN MANAGEMENT
(2016)
Article
Management
Ian Y. Blount, James A. Hill
JOURNAL OF PURCHASING AND SUPPLY MANAGEMENT
(2015)
Article
Business
Ian Y. Blount, Delmonize A. Smith, James A. Hill
JOURNAL OF DEVELOPMENTAL ENTREPRENEURSHIP
(2013)
Article
Management
Stephanie Eckerd, James A. Hill
INTERNATIONAL JOURNAL OF OPERATIONS & PRODUCTION MANAGEMENT
(2012)
Article
Management
Zhen He, James Hill, Ping Wang, Gang Yue
TOTAL QUALITY MANAGEMENT & BUSINESS EXCELLENCE
(2011)
Article
Business
Kathryn A. Marley, Peter T. Ward, James A. Hill
SUPPLY CHAIN MANAGEMENT-AN INTERNATIONAL JOURNAL
(2014)
Article
Management
Larry J. LeBlanc, James A. Hill, Jerry Harder, Gregory W. Greenwell
JOURNAL OF BUSINESS LOGISTICS
(2009)
