A mathematical model for production planning in hybrid manufacturing-remanufacturing systems

Chen, M.; Abrishami, P.

doi:10.1007/s00170-013-5538-0

Cited by 38 publications

(13 citation statements)

References 14 publications

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“…Even in the worst-case scenarios (19)(20)(21)(22)(23)(24)(25)(26)(27), service level is high, around 98 % (see Tables 5 and 6 for JSCM and SSCM, respectively). This result was expected because the manufacturing and remanufacturing capacities are sufficient to process at least 85 % of the highest demand.…”

Section: Results Of the Stochastic Modelsmentioning

confidence: 99%

“…Moreover, the difference between the service levels of both models is negligible-99.29 % in JSCM and 99.23 % in SSCM. These results suggest that both models prioritize meeting "worstcase" demands (i.e., demands of scenarios [19][20][21][22][23][24][25][26][27] in an attempt to avoid high backlogging costs, but incurring in a large amount of products in stock. If models prioritized meeting "average" demands, inventory levels would decrease, but at the expense of a substantial deterioration of the service levels of the scenarios 19-27. In fact, in low-demand scenarios (1-9), serviceable inventory is higher because the production variables are defined in the first-stage in an attempt to meet all demands until the last period, causing the aforementioned large inventory.…”

Section: Results Of the Stochastic Modelsmentioning

confidence: 99%

“…The proposed models were solved by dynamic programming and heuristics approaches. Several papers focused on solution methods for similar lot-sizing problems with remanufacturing, as these problems are usually NP-hard, e.g., Schulz [19], Li et al [20], Ahn et al [21], Parsopoulos et al [22], Sifaleras and Konstantaras [23], Baki et al [24], and Chen and Abrishami [25].…”

Section: Literature Review On Remanufacturing Lot-sizing Problemsmentioning

confidence: 99%

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Hybrid manufacturing and remanufacturing lot-sizing problem with stochastic demand, return, and setup costs

Macedo

Alem

Santos³

et al. 2015

Int J Adv Manuf Technol

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This paper presents mixed-integer programming models to hybrid manufacturing and remanufacturing lotsizing problems in which remanufactured products are treated as new ones, so that both manufactured and remanufactured products compete to meet the demands. Differently from previous studies, we consider an environment with multiple products, both manufacturing and remanufacturing costs, disposal, backlogging, and the inherent uncertainties of demands, return rates of usable products, and setup costs. In order to deal with these uncertainties, we propose a scenario-based two-stage stochastic programming model that assumes production and setup as first-stage decision variables, whereas inventory, disposal, and backlogging are defined as second-stage decision variables.We also analyze a risk-averse model in an attempt to reduce the dispersion of the second-stage costs. The main results of the present study indicate that setup costs for remanufacturing can be decisive in choosing between manufacturing or remanufacturing. Even though remanufacturing costs are lower, the process is still largely dependent on return rates and low storage costs for returned products.

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Section: Results Of the Stochastic Modelsmentioning

confidence: 99%

Section: Results Of the Stochastic Modelsmentioning

confidence: 99%

Section: Literature Review On Remanufacturing Lot-sizing Problemsmentioning

confidence: 99%

See 1 more Smart Citation

Hybrid manufacturing and remanufacturing lot-sizing problem with stochastic demand, return, and setup costs

Macedo

Alem

Santos³

et al. 2015

Int J Adv Manuf Technol

View full text Add to dashboard Cite

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“…In contrast to the classical lot-sizing problem, one of the main specificities of LSR lies on the demand, that can be fulfilled from a single stream of serviceable products or be fitted into two categories of newly produced and remanufactured ones. Even if no distinction is commonly made between manufactured and remanufactured products, there exist some studies that considered the market divided into new and remanufactured segments (Koken et al, 2018a,b;Zhang et al, 2011;Chen and Abrishami, 2014). To go further, Piñeyro and Viera (2010) allowed the substitution of remanufactured products by the new ones for absorbing the fluctuations in the quantity of product returns.…”

Section: Mathematical Formulationmentioning

confidence: 99%

Towards circular economy in production planning: Challenges and opportunities

Suzanne

Absi

Borodin

2020

European Journal of Operational Research

107

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In the actual era of the international trade, global warming and depletion of Earth's natural resources, the willingness to generate sustainable and competitive benefits determines us to stop thinking linearly (produce, consume and dispose) and to shift towards a circular approach by closing material loops. The latter falls within the concept of circular economy that, in turn, derives from reverse logistics. This paper proposes a comprehensive state-of-the-art review around the topic of circular economy and reverse logistics with a particular emphasis on mid-term production planning under discrete time settings. The broad spectrum of reviewed publications is categorized and discussed with respect to the main recovery operations, namely: (i) disassembly for recycling, (ii) from product to raw material recycling, and (iii) by-products and co-production. For each of the aforementioned recovery options, this paper elucidates the related definitions, reviews the mathematical formulations jointly with a structured overview of the solution methods, and discusses their industrial implications. Given the legislative pressure to mitigate environmental impacts caused by production processes, a special attention is paid to the greenhouse gas emissions and energy consumption. A cross-cutting analysis of the reviewed literature brought forward a number of research gaps and revealed multiple research opportunities to support the development of the circular economy. The key findings show an ever growing interest in making sustainable the traditional linear industrial processes within a circular economy context.

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“…It is regarded as the process of transforming used products to a "like-new" functional state matched with warranty [1]. It is commonly referred to as product recovery or reuse processes which consist of reconditioning and repairing of used components to achieve a new state.…”

Section: Introductionmentioning

confidence: 99%

A holistic framework for evaluation and selection of remanufacturing operations: an approach

Kafuku

Saman

Yusof

et al. 2016

Int J Adv Manuf Technol

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Lack of efficient evaluation methods to help decision makers in making informed decision regarding in-house technology investments, outsourcing technology, and manual activities in the remanufacturing industry has raised serious concerns in the selection process of technologies based on company size and resources. This has resulted in the inability of decision makers to broadly assess the scope of alternative technologies against remanufacturing processes. Thus, it has resulted in the choice of a common solution based on inconsistencies and uncertainties. This paper proposes a holistic framework that can assist decision makers in evaluating the remanufacturing operations by offering better understanding of the performance and potential capabilities in the selection of appropriate technology. The salient feature of the proposed framework is its utilization of the fuzzy logic method as guiding tool to analyze criteria for technology selection in order to make informed decisions on whether to invest or outsource a technology or use labor-intensive operations to the specific process. The paper also highlights importance of the technology assessment framework in aligning and consolidating the dedicated thinking for the life cycle of the particular technology. The major contribution of the framework is its integration of obsolete and disposal phases with the acquisition and adoption phases. Therefore, during technology assessment, decision makers are guided by a step-by-step iterative process on technology requirement verification.

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A mathematical model for production planning in hybrid manufacturing-remanufacturing systems

Cited by 38 publications

References 14 publications

Hybrid manufacturing and remanufacturing lot-sizing problem with stochastic demand, return, and setup costs

Hybrid manufacturing and remanufacturing lot-sizing problem with stochastic demand, return, and setup costs

Towards circular economy in production planning: Challenges and opportunities

A holistic framework for evaluation and selection of remanufacturing operations: an approach

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