Special Issue "Research on Environment of the Industry 4.0 Implementation and Operations Management"

Dear Colleagues,

This Special Issue will provide a multidisciplinary forum for those involved in the fields of management and industrial engineering. Scientists and practitioners pay a lot of attention to the technological aspects of Industry 4.0, but relatively little research has been conducted on the issue of operations management. Thus, the main aim of this Special Issue is to explore various approaches and methods of operations management, which will lead to achieving many measurable business benefits of Industry 4.0 implementation.

The application of modern technologies such as the Internet of things, big data analytics, cloud computing, etc. should increase revenues resulting from the individualization of products closely tailored to customer needs and from business scaling. Therefore, enterprises can support Industry 4.0 solutions to create new business models, open up new forms of sales and service channels and monitor and control costs very carefully. The submission of the latest original research, achievements and developments in the form of theoretical and applied papers, as well as critical reviews of the extant literature, are welcomed. The Special Issue will generally cover issues related to the possibilities of using the existing methods of operations management and adapting them to the Industry 4.0 environment as well as proposals for new business models and new methods to support this concept.

Prof. Dr. Anna Saniuk
Guest Editor

Manuscript Submission Information

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• Industry 4.0
• business models
• methods and tools for the measurement and control of the efficiency of Industry 4.0 solutions
• human resource management
• production management
• project management
• process management
• controlling
• supply chain management
• maintenance management
• total quality management
• sustainable management
• decision support systems
• JiT and lean operations

Title: Development of a lean manufacturing framework to strengthen the reliability of production control in industry 4.0
Authors: Varun Tripathi1; S Chattopadhyaya2; Shubham Sharma3*; Jujhar Singh3; Changhe Li4; Danil Yu Pimenov5; Sunpreet Singh6; Khaled Giasin7
Affiliation: 1Department of Mechanical Engineering, Accurate Institute of Management & Technology, Greater Noida-(UP), India. 2Indian Institute of Technology (ISM), Dhanbad, India. 3Deptt. of Mechanical Engg., IK Gujral Punjab Technical University, Main Campus-Kapurthala 144603, India. E-Mail: [email protected], [email protected] (S.S.) 4School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao, 266520, China. 5Department of Automated Mechanical Engineering, South Ural State University, Lenin Prosp. 76, Chelyabinsk 454080, Russia; [email protected] (D.Y.P.) 6Department of Mechanical Engineering, National University of Singapore, Singapore 119077, Singapore 6School of Mechanical and Design Engineering, University of Portsmouth, Portsmouth PO1 3DJ, UK. [email protected] (K.G.) *Correspondence: [email protected] (S.S.); [email protected] (K.G.)
Abstract: Lean manufacturing has established itself as one of the problem-solving keys in production shop floor management in industry 4.0. The Lean manufacturing is used for maximization of productivity by elimination of non-value-added activities on the shop floor. The main objective of the present research article is to develop a methodology for enhancement in the reliability of production control by lean manufacturing in industry 4.0. The developed methodology has been validated by achieved productivity enhancement in a case example of a machinery assembly unit. The result showed that the developed methodology with lean manufacturing has been enhanced the productivity level within available resources. The authors of the present article strongly believe that the present work could be beneficial for young researchers and industry persons to improve in production control in industry 4.0. Keywords: Lean manufacturing, Value stream mapping, Industry 4.0, Reliability, Production control.

Title: An agile system to enhancement in productivity through a modified value stream mapping approach in industry 4.0: A novel approach
Authors: Varun Tripathi1; S Chattopadhyaya2; Alok Bhadauria3; Shubham Sharma4*; Changhe Li5; Danil Yu Pimenov6; Khaled Giasin7*; Sunpreet Singh8; Girish Dutt Gautam9
Affiliation: 1Department of Mechanical Engineering, Accurate Institute of Management & Technology, Greater Noida-(UP), India. 2Indian Institute of Technology (ISM), Dhanbad, India. 3Department of Materials Science and Engineering, Indian Institute of Technology, Kanpur. 4Deptt. of Mechanical Engg., IK Gujral Punjab Technical University, Main Campus-Kapurthala 144603, India. E-Mail: [email protected], [email protected] (S.S.) 5School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao, 266520, China. 6Department of Automated Mechanical Engineering, South Ural State University, Lenin Prosp. 76, Chelyabinsk 454080, Russia; [email protected] (D.Y.P.) 7School of Mechanical and Design Engineering, University of Portsmouth, Portsmouth PO1 3DJ, UK. [email protected] (K.G.) 8Department of Mechanical Engineering, National University of Singapore, Singapore 119077, Singapore 9Mangalmay Institute of Engineering & Technology, Greater Noida, India. Corresponding author(s): [email protected] (S.S.); [email protected] (K.G.)
Abstract: The worldwide industries are emphasizing on development of an agile system to enhance productivity in the industry. So that it can be applied to improvement in all production conditions in industry 4.0. In the present scenario, several methods are used for improvement in production like value stream mapping, kaizen, just in time, Kanban, total productive maintenance, etc., The objective of the present research article is to make an agile system to improvement in productivity level in industry 4.0 through a methodology coupled with value stream mapping. Value stream mapping is a lean-based method and used for maximization in productivity level by elimination of non-value-added activities. The proposed methodology has been validated by productivity enhancement achieved in a case study on the earthmoving machinery manufacturing unit. The study establishes that the proposed methodology could encourage the industry personals during the decision-making for improvement in production in industry 4.0.