Simulation to Enable a Data-Driven Circular Economy

TLDR

This study investigates how digital‑technology‑driven simulation can accelerate circular manufacturing in the UK by extending product life and informing optimal lifecycle interventions. The authors mapped and simulated a remanufacturing facility with discrete‑event simulation, identified variability in returned product condition through interviews, and introduced a certainty‑of‑product‑quality metric tested in system‑dynamics and DES models to optimize inspection and processing times. Applying CPQ enables cost‑saving automated inspection, precise go/no‑go decisions, and supports circular‑economy strategies by determining the best intervention—upgrade, refurbish, remanufacture, or recycle—at each product life stage.

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.