# A Review on the Lifecycle Strategies Enhancing Remanufacturing
## 2 Methodology
None of the strategies seemed to be fading with time, they were instead gaining more interest but at different frequencies. EoL product collection was number 1 both between 1995 and 2000 and 2016 and 2021, with CLSC as number 2, with 17 papers during the last period, whereas product service system dropped from number 3 to last over time and predetermined remanufacturing time climbed from last position between 1995 and 2000 (0 papers) to third position in the last period (2016-2021) with 16 papers. Reverse logistics came in at the fourth position with 15 papers in the last period, after dropping from first position during the first period. Product lifecycle data climbed from 1995-2000 (0 papers) to fifth position in the last period with 13 papers. RUL publications increased at a much slower rate and remained at number 6 in the last period with 12 papers. DfRem was at number 7, with a slower progress from 2 papers in the first period to 11 papers in the last period. The recent trends were identified based on the frequency of publication of innovative techniques to enhance remanufacturing, especially for papers which emphasized digitalized strategies to better remanufacturing. Trending terms like \"Internet of Things\" (IoT), \"big data\", \"artificial intelligence\" (AI) and \"5G network\" were coded with remanufacturing and the publications that used any of the terms in remanufacturing were taken into consideration. Figure 4 below shows the number of papers identified for each trending strategy. We can observe that the frequency was in the following order: industry4.0, COBOTs, upgrading, additive manufacturing, smart remanufacturing and finally SRDM. These trends are discussed in this order in Section 4. Figure 2: History of relevant publications. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Strategies** & **Relevant Papers** & **Case Study Used** \\ \hline \hline EoL product collection & [30] & Electronic products \\  & [31] & Emphasis on remanufacturing \\  & [32] & Mobile phones \\  & [33] & WEEE \\ CLSC & [34] & OEMs \\  & [35] & Electric vehicle batteries \\  & [36] & System dynamics analysis \\  & [37] & Paper recycling \\ Predetermined remanufacturing timing & [38] & Manufacturing systems \\  & [39] & Multi-scale PCA \\  & [40] & Wind turbines \\ RUL & [41] & Used parts \\  & [40] & Wind turbines \\  & [42] & Aircraft engines \\  & [43] & Railway D-cables \\ Reverse logistics & [44] & Cell phones \\  & [45] & Use of algorithm in Taoyuan City \\  & [46] & Improved genetic algorithm \\  & [47] & Chinese automobile parts \\ DfRem & [48] & Dissassembly line balancing \\  & [49] & Analyzing operational factors \\  & [50] & Analytic network process \\ Product lifecycle data & [51] & Quality grading and end-of-use recovery \\  & [52] & IoT scheduling to predict remanufacturing timing \\  & [53] & Big data in product lifecycle \\ PSS & [54] & Baby grams \\  & [55] & Upgradable PSS \\ Collaborative robots & [56] & Human-robot collaborative disassembly cell \\  & [57] & Enhanced discrete bee algorithm \\  & [58] & Maintenance of autonomous train \\  & [59] & A study on attitude and acceptance in an industrial context \\ Additive manufacturing & [60] & Metals (silserv, iron, etc.) \\  & [61] & Future outlook for remanufacturing \\ Industry 4.0 & [62] & Inter-country comparative perspective \\  & [63] & Use of augmented reality \\ Upgrading products & [64] & EoL. fires \\  & [65] & PSS \\ SRDM & [66] & Algorithm to optimize disassembly \\ Smart remanufacturing & [67] & 14.0 and CE \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Case studies used in various strategies. Figure 3: Evolution of strategies over the years. The rest of this review is presented as shown in Figure 5 below. It is organized to clearly show what questions are asked and the proposed solutions. Section 3 highlights the lifecycle strategies that enhance remanufacturing and how they increase the remanufacturability of a product.