Computers & Industrial Engineering: An International Journal

Special Issue on

Smart Manufacturing, Innovative Product and Service Design to Empower Industry 4.0

Aims of the Special Issue:

With the new paradigm of Industry 4.0, the manufacturing and service industries are increasingly adopting smart equipment and intelligent system with multimode sensors and more attention has been drawn to develop Cyber-Physical Systems, the Internet of Things (IoTs), and big data analytics for improving the operational performance. In particular, various solutions and techniques have been developed to extract useful information and derive effective manufacturing intelligence with advanced decision technologies to address new challenges of recent progress in smart manufacturing and operational excellence. Thus, this special issue of the Computers& Industrial Engineering (C&IE)aims to address emergent research issues regarding how to adopt new technologies for smart production, digital manufacturing, and innovative design and service to empower Industry 4.0.

Scope of the Special Issue:

A main source of the manuscripts in this special issue will be expanded versions of papers selected from those published in the proceedings of the 46th International Conference on Computers & Industrial Engineering (CIE46), Tianjin, China, October29 – October 31,2016.Other papers describing scientific technologies and methodologies that improve the quality of business and operations decisions toward Industry 4.0 are also welcome and can be directly submitted for regular review and potential publication in this special issue.This special issue will focus on the state-of-art of Industry 4.0, Internet of Things, and big data for manufacturing and service industry and explore how the emerging technologies utilize the concept of smart production, digital manufacturing, and innovative design and service in manufacturing and service industry. Submissions of scientific results from experts in academia and industry worldwide are strongly encouraged. The topics of interest include, but are not limited to:

  • Advanced process control/ Advanced equipment control (APC/AEC)
  • Intelligent systems
  • Automated material handling systems (AMHS) routing & scheduling
  • Big data analytic and applications
  • Computational intelligence for smart manufacturing
  • Data mining for yield and production improvement
  • Data science and machine learning for smart manufacturing
  • Decision support systems (DSS)
  • Decision technologies for smart manufacturing
  • Equipment diagnosis and predictive maintenance
  • Equipment productivity improvement
  • Factory modeling, analysis and performance evaluation
  • Industry 4.0 and Cyber-Physical Systems
  • Intelligent cooperation to resource planning & allocation
  • Internet of Things (IoTs) and multi-mode sensors
  • Manufacturing innovation
  • Manufacturing intelligence & manufacturing informatics
  • Mobile and wireless applications (RFID)
  • Product design and virtual design
  • Service innovation
  • Yield enhancement systems and e-Diagnosis
  • Product and process optimization based on IoT and big data analytics

Submission Guidelines:

All papers must be original and not published, submitted nor currently under review elsewhere. All manuscripts should be submitted through the Elsevier’s online system at Please choose “Smart Manufacturing for Industry 4.0” as Section/Category when assigning the Article type. In preparing their manuscript, authors are asked to closely follow the “Instructions to Authors”.Submissions will be reviewed according to C&IE’s rigorous standards and procedures through double-blind peer review by at least two qualified reviewers. Accepted papers become the property of C&IE’s publisher, Elsevier.

Publication Schedule (tentative):

Deadline for manuscript submission: 30 June, 2017

Review report: 31 October, 2017

Revised paper submission deadline: 31December, 2017

Notification of final acceptance: 30 January, 2018

Approximation publication date: March, 2018

Guest Editors:

  • Prof. Runliang Dou*, Tianjin University E-mail: Guest Editor)
  • Prof. Zhen He, Tianjin University E-mail:
  • Prof. Chia-Yu Hsu, Yuan Ze University E-mail:



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