Simulation to Enable a Data-Driven Circular Economy

Fiona Charnley, Divya Tiwari, Windo Hutabarat, Mariale Moreno, Okechukwu Okorie and Ashutosh Tiwari
Additional contact information
Fiona Charnley: Exeter Centre for the Circular Economy, University of Exeter, Rennes Drive, Exeter EX4 4PU, UK
Divya Tiwari: Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK
Windo Hutabarat: Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK
Mariale Moreno: Centre for Competitive Creative Design, Cranfield University, Bedfordshire MK43 0AL, UK
Okechukwu Okorie: Exeter Centre for the Circular Economy, University of Exeter, Rennes Drive, Exeter EX4 4PU, UK
Ashutosh Tiwari: Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK

Sustainability, 2019, vol. 11, issue 12, 1-16

Abstract: This paper presents an investigation on how simulation informed by the latest advances in digital technologies such as the 4th Industrial Revolution (I4.0) and the Internet of Things (IoT) can provide digital intelligence to accelerate the implementation of more circular approaches in UK manufacturing. Through this research, a remanufacturing process was mapped and simulated using discrete event simulation (DES) to depict the decision-making process at the shop-floor level of a remanufacturing facility. To understand the challenge of using data in remanufacturing, a series of interviews were conducted finding that there was a significant variability in the condition of the returned product. To address this gap, the concept of certainty of product quality (CPQ) was developed and tested through a system dynamics (SD) and DES model to better understand the effects of CPQ on products awaiting remanufacture, including inspection, cleaning and disassembly times. The wider application of CPQ could be used to forecast remanufacturing and production processes, resulting in reduced costs by using an automatised process for inspection, thus allowing more detailed distinction between “go” or “no go” for remanufacture. Within the context of a circular economy, CPQ could be replicated to assess interventions in the product lifecycle, and therefore the identification of the optimal CE strategy and the time of intervention for the current life of a product—that is, when to upgrade, refurbish, remanufacture or recycle. The novelty of this research lies in investigating the application of simulation through the lens of a restorative circular economic model focusing on product life extension and its suitability at a particular point in a product’s life cycle.

Keywords: circular economy; circular 4.0; remanufacturing; discrete event simulation (DES); system dynamics (SD) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

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