Industry 4.0 has come as a consecutive and predicted outcome of the previous industrial periods, recently dubbed Industry 1.0, 2.0 and 3.0 (Pereira and Romero, 2017). As an expected outcome, the companies were proactively prepared for the transformational potential of this opportunity by defining in advance the most suitable manufacturing models, operational processes and targets –coming prepared for the associated challenges (Almada-Lobo, 2016; Pereira and Romero, 2017). From a technical perspective, the context of Industry 4.0 can be described as ‘increased digitisation and automation in addition to increased communication enabled by the creation of a digital value chain’ (Oesterreich and Teuteberg, 2016, p. 122). While not a fully agreed term, ‘Industry 4.0’ is still a ‘slippery’ concept (Pereira and Romero, 2017), however undoubtedly the term ‘Industry 4.0’ is an evolving trend and attracted increasing interest from both practitioner and academic communities (Liao et al., 2017; Fatorachian and Kazemi, 2018). Industry 4.0 primarily includes the internet of things (IoT), cloud and cognitive computing, and digital manufacturing and cyber-physical systems that collect, transfer and make sense of Big Data (Zhou et al., 2015) in order to develop smart industries and respond to fluctuations in the markets’ demands for high-quality products. Industry 4.0 has been used in manufacturing and in the car industry by companies such as BMW and Jaguar Land Rover, and also in the food industry by companies such as Mondelez and Nestlé to enhance their overall operational efficiency.
While literature has acknowledged the power of Big Data and the implied disruption in the product and service models (Baines et al., 2017; Papadopoulos et al., 2017; Spanaki et al., 2018; Yoo et al., 2012), Industry 4.0 implies a wave of innovation. There are potential opportunities for organizations and supply chains to innovate, to create strategic advantage and to generate new business value from the data (Gandomi and Haider, 2015), but a rigorous approach of the associated disruption is still missing (Fatorachian and Kazemi, 2018; Santos et al., 2017). The purpose of this Special Issue is to facilitate an ongoing discussion for researchers or practitioners, to showcase their findings, and to explore the implementation of advanced and emerging technologies in the next generation of manufacturing and the wider implications of Industry 4.0 in production planning and operations management. Original research contributions, case studies and/or reviews are invited for this SI.
Suggested topics of interest include, but are not limited to:
- The impact of Industry 4.0 on operational efficiency, productivity and performance.
- The use of Big Data through IoT for smart and responsive manufacturing operations.
- The impact of Industry 4.0 on operations management for products and services.
- Data heterogeneity, quality, privacy, and security issues for operations managers in Industry 4.0
- The disruptive potential of Industry 4.0 in production processes, planning and control.
- Human-centred focus of Industry 4.0 in terms of resources, capabilities and skills required for employees in the industrial sectors
- Contextual and sector differences in the adoption of Industry 4.0 technologies and business models
- The role of product and/or service complexity in the adoption of Industry 4.0
All submitted papers should address issues related to the theme of the SI that also fall within the scope of the Production Planning & Control particularly with regard to industry relevance. This special issue will focus on publishing original research papers dealing with studies that examine emerging concepts in production, procurement, and logistics in industry. Case research that builds and validates theory in various contexts is particularly encouraged.
Manuscripts should be submitted by 31st May 2019 and should strictly follow the “Guide for Authors” of the journal. Submitted articles will first be evaluated by the guest editors to ensure suitability in terms of scope of both the special issue and the journal. Suitable papers will be single-blind reviewed as per the journal’s standard practice.
Please prepare your papers to Production Planning & Control publication standards available at: http://www.tandfonline.com/action/authorSubmission?journalCode=tppc20&page=instructions .
All submissions should be made online at the Production Planning & Control Scholar One Manuscripts website (https://mc.manuscriptcentral.com/tppc ). New users should first create an account. Once logged on to the site, submissions should be made via the Author Centre. Online user guides and access to a helpdesk are available on this website. Please register your paper with the code “SI” at the beginning of the Title field. Papers will undergo a single blind review. Submitted papers must not have been previously published nor be currently under consideration for publication elsewhere. Reviewing and selection of papers will be carried out according to the standards of Production Planning & Control.
- Guest Editor: Thanos Papadopoulos, Kent Business School, University of Kent, UK (email@example.com)
- Guest Editor: Surya Prakash Singh, Department of Management Studies. Indian Institute of Technology Delhi, New Delhi-110016, India. (firstname.lastname@example.org)
- Guest Editor: Konstantina Spanaki, School of Business and Economics, Loughborough University, UK (K.Spanaki@lboro.ac.uk)
- Guest Editor: Angappa Gunasekaran, Dean, School of Business and Public Administration, California State University, Bakersfield, USA. (email@example.com)
- Guest Editor: Rameshwar Dubey, Montpellier Business School, Montpellier Research in Management, 2300 Avenue des Moulins, 34000 Montpellier France. (firstname.lastname@example.org)