Exploring the Linkages Between the Internet of Things and Planning and Control Systems in Industrial Applications

The potential of the Internet of Things (IoT) and other technologies in the realm of Industry 4.0 to generate valuable data for monitoring the performance of the production processes and the whole supply chain is well established. However, these large volumes of data can be used within planning and control systems (PCSs) to enhance real-time planning and decision-making. This paper conducts a literature review to envisage an overall system architecture that combines IoT and PCS for planning, monitoring and control of operations at the level of an industrial production process or at the level of its supply chain. Despite the extensive literature on IoT implementations, few studies explain the interactions between IoT and the components of PCS. It is expected that, with the increasing digitization of business processes, approaches with PCS and IoT become ubiquitous in the near future.

[1]  Haoyu Wang,et al.  Managing Traditional Solar Greenhouse With CPSS: A Just-for-Fit Philosophy , 2018, IEEE Transactions on Cybernetics.

[2]  Naiqi Wu,et al.  IoT-Enabled Real-Time Production Performance Analysis and Exception Diagnosis Model , 2016, IEEE Transactions on Automation Science and Engineering.

[3]  Mehmet Bayram Yildirim,et al.  An energy-aware multiobjective ant colony algorithm to minimize total completion time and energy cost on a single-machine preemptive scheduling , 2019, Comput. Ind. Eng..

[4]  Partha Pratim Ray.  A survey on Internet of Things architectures , 2018, J. King Saud Univ. Comput. Inf. Sci..

[5]  Oliver Riedel,et al.  Production planning and control systems – a new software architecture Connectivity in target , 2019 .

[6]  Ullah Saif,et al.  Drum buffer rope-based heuristic for multi-level rolling horizon planning in mixed model production , 2019, Int. J. Prod. Res..

[7]  Stefan Seuring,et al.  From a literature review to a conceptual framework for sustainable supply chain management , 2008 .

[8]  Shailesh Chandra,et al.  Impact assessment of the Internet of Things on feeder transit performance , 2018 .

[9]  Dimitris Mourtzis,et al.  A cloud-based cyber-physical system for adaptive shop-floor scheduling and condition-based maintenance , 2018 .

[10]  Yung Po Tsang,et al.  An intelligent model for assuring food quality in managing a multi-temperature food distribution centre , 2018, Food Control.

[11]  Ming Li,et al.  Synchronisation for smart factory - towards IoT-enabled mechanisms , 2017, Int. J. Comput. Integr. Manuf..

[12]  W. Tsai,et al.  A Framework of Production Planning and Control with Carbon Tax under Industry 4.0 , 2018, Sustainability.

[13]  J. Y. Lee,et al.  The FaaS system using additive manufacturing for personalized production , 2018, Rapid Prototyping Journal.

[14]  Sang Do Noh,et al.  Implementation of Cyber-Physical Production Systems for Quality Prediction and Operation Control in Metal Casting , 2018, Sensors.

[15]  George Q. Huang,et al.  Cloud-enabled real-time platform for adaptive planning and control in auction logistics center , 2015, Comput. Ind. Eng..

[16]  P. Helo,et al.  ICT-based solution approach for collaborative delivery of customised products , 2016 .

[17]  Aleksandr Ometov,et al.  A Harmonized Perspective on Transportation Management in Smart Cities: The Novel IoT-Driven Environment for Road Traffic Modeling , 2016, Sensors.

[18]  Yingfeng Zhang,et al.  A big data driven analytical framework for energy-intensive manufacturing industries , 2018, Journal of Cleaner Production.

[19]  José Boaventura-Cunha,et al.  Digital Technologies for Forest Supply Chain Optimization: Existing Solutions and Future Trends , 2018, Environmental Management.

[20]  Gerben G. Meyer,et al.  Production monitoring and control with intelligent products , 2011 .