Inventory Optimization of Deteriorating Items: A Comprehensive Review of Carbon-Control Policies and Their Impact on Shelf Life, Greening Effects, and Rework Policies

[EN] This study examines the deteriorating inventory management problem for items with short shelf life, considering alternative carbon control strategies from 2018 to 2023. These policies include carbon cap and trade, trade and credit policy, carbon-emission control, and others. The study takes into account critical elements such as shelf life, optimal policies, modelling approaches, greening effects, subsidies, and rework policies. The analysis started with a search for 'EOQ Model' in the Science Direct database, which generated 788 items. For a comprehensive evaluation, were restricted our resources to 329 scientific publications, including deterioration. Following that, it was limited to carbon emissions, obtaining 123 results. The papers referenced above cover a wide range of issues, including remanufacturing and rework, as well as carbon caps and trade-credit systems for data collection, yielding 45 and 32 research articles, respectively. The review prioritizes respected publications of peer-reviewed journals papers for reliable results were examined. A review of the literature suggested that future research should concentrate on stochastic modelling. The emphasis has been placed on identifying future study gaps that will aid in the development of most relevant models. The current work will serve as a guideline for selecting the suitable mathematical technique(s) and methodology(s) in various situations involving deteriorating items. The current analysis examined 42 research papers on deteriorating inventory modelling accessible in the literature to characterize its current state and indicate probable future directions. Future research needs have also been identified. This comprehensive study is firmly believed to fill a knowledge gap on deteriorating inventory and support in the formulation of appropriate methods for the creation of a successful and effective inventory control system for deteriorating products.Verma, P.; Mishra, VK. (2023). Inventory Optimization of Deteriorating Items: A Comprehensive Review of Carbon-Control Policies and Their Impact on Shelf Life, Greening Effects, and Rework Policies. WPOM-Working Papers on Operations Management. 15(1):39-56. https://doi.org/10.4995/wpom.20268395615

Investigation On The Influence Of Remanufacturing On Production Planning And Control – A Systematic Literature Review

Production planning and control (PPC) is one of the focal operational tasks of a company, and it is used to design logistics services in a target-orientated manner so that individual customer requirements can be fulfilled. However, existing PPC framework models are still based on the prevailing linear economic procedure (take - make - dispose). Due to customers' increasing interest in sustainability and growing regulatory pressure, the Circular Economy (CE) meets these changing conditions by closing material cycles, improving resource efficiency and extending product life cycles. However, for a company to guarantee a high logistics performance, the operational PPC must be adapted to this new economic model. To this end, it needs to be investigated whether and how the adaptation of circular strategies influences existing PPC processes. This paper focuses on the circular strategy of remanufacturing and its influence on different PPC-main tasks. The latter will be examined using a systematic literature review. Finally, the results of this analysis are compared with the Hanoverian Supply Chain Model as a PPC framework model. This comparison shows which PPC tasks are affected and which existing approaches have already been developed. Ultimately, these results provide the basis for developing a framework model for operational PPC regarding the CE

Commande optimale stochastique des systèmes manufacturiers en boucle fermée

Le travail présenté dans cette thèse vise à développer conjointement des stratégies optimales pour contrôler la production et la maintenance dans un système manufacturier hybride intégrant la refabrication et en présence des incertitudes. Les pannes et réparations des machines, la demande des clients, le retour des produits en fin de vie, la détérioration des machines et de la qualité des produits fabriqués constituent les principales sources d’incertitudes considérées dans cette thèse. La prise en compte de tous ces aspects aléatoires rend le problème d’optimisation très complexe. Nous allons donc diviser ce problème en cinq (5) sous-problèmes en intégrant progressivement ces aspects pour mieux comprendre leurs impacts sur les politiques de commande. Les contributions de cette thèse sont présentées en cinq (5) phases. La première phase est l’étude d’un problème de planification des activités de production et de remplacement d’un système manufacturier dans un contexte de détérioration. Les phénomènes aléatoires examinés dans cette phase sont les pannes et les réparations de la machine. Nous supposons que la machine subit une détérioration progressive pendant son fonctionnement et que le taux de panne de la machine est une fonction de son âge. En cas de panne de la machine, des réparations minimales sont effectuées. Lorsque la machine attaint un certain niveau de dégradation, elle est remplacée. En raison de réparations minimales, la dynamique du système est affectée par son historique et les processus semi-Markoviens ont été utilisés pour la modélisation. Une résolution numérique des conditions d’optimum, décrites par les équations d’Hamilton-Jacobi-Bellman (HJB), a conduit à la solution du problème étudié. La deuxième phase de l’étude permet d’intégrer dans le système de production de la première les aspects aléatoires au niveau de la demande des clients et de la qualité des pieces produites. L’effet du phénomène de détérioration sur la machine, causé par les processus de vieillissement et de réparation minimale, est principalement observé dans sa disponibilité et dans la qualité des pièces produites. Nous considérons que le taux de défaillance et le taux de rejets dépendent de l’âge de la machine. L’intégration des comportements aléatoires de la demande et de la qualité nous a amené à proposer une nouvelle approche de modélisation en développant les conditions d’optimum de second ordre de type d’HJB. Les politiques de commande optimale sont déterminées par des méthodes numériques. Dans la troisième phase, nous avons étudié un système hybride constitué d’une (1) machine de fabrication et d’une (1) machine de refabrication. Les machines sont non identiques et non fiables. La modélisation de leur dynamique a été faite en utilisant les chaînes de Markov homogènes. En plus des incertitudes des deux (2) phases précédentes, nous considérons les incertitudes sur la demande des clients et sur les retours de produits. La solution a été obtenue numériquement par la résolution des équations d’HJB de second ordre, et nos résultats ont été confirmés par une analyse numérique. Dans la quatrième phase de ce travail, nous avons tenu compte de la détérioration de la machine de refabrication dans le cadre d’un système hybride fabrication/refabrication. Nous avons considéré dans cette phase les systèmes de production dans lesquels la nature hétérogène des produits retournés implique un processus de réparation imparfaite sur la machine. En plus de cette détérioration, les machines sont sujettes à des pannes et reparations aléatoires. Une nouvelle approche de modélisation mathématique est proposée pour traiter une classe de problèmes reliés à l’historique des machines. Cette nouvelle approche est base sur l’extension de l’espace d’état et conduit à un modèle de décision Markovien; ce qui nous permet d’appliquer les techniques puissantes développées pour l’optimisation stochastique de ces modèles. Ensuite, les politiques de fabrication, de refabrication et de remplacement ont été déterminées par les mêmes outils numériques que ceux des phases précédentes. Des analyses de sensibilité ont été élaborées pour montrer la pertinence de l’approche proposée. La cinquième phase complète les modèles précédents, puisque nous étendons le concept de l’effet de détérioration du système hybride sur les deux (2) machines pour résoudre des problèmes industriels plus réalistes et de nature complexe. La première machine traite les activités de fabrication, et son effet de détérioration affecte de façon aléatoire sa disponibilité et la qualité de ses pièces produites. La deuxième machine traite les activités de rectification des produits défectueux de la première machine et de refabrication des produits retournés en fin de vie. L’effet de détérioration sur la disponibilité de la machine de rectification/refabrication est généré par le flux des mauvaises pièces traitées. Puisque la détérioration de la première machine a pour effet de causer des pannes sur la deuxième machine, elle devra être remplacée par une nouvelle machine qui permet de restaurer les paramètres du système hybride aux conditions initiales lorsqu’un certain niveau de dégradation sera atteint. L’objectif est de déterminer le plan de production optimale, pour la fabrication, la rectification et la refabrication, ainsi que la stratégie de remplacement tout en minimisant le coût total. Puisque le processus de détérioration conduit vers un processus avec la notion de mémoire, nous avons développé un modèle de décision semi-Markovien pour décrire cette dynamique. Les conditions d’optimum de type HJB de second ordre ont été résolues par des méthodes numériques et la structure de la politique de commande conjointe a été validée par une analyse de sensibilité

The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three ‘pillars’ of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a ‘boomerang’ effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the well-developed research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems

Production distribution planning in a multiechelon supply chain using carbon policies: A review and reflections

Sustainability of a supply chain has gained more attention from economists, environmentalists, consumers, manufacturers, government and the academia. In this paper, the literature survey has been performed on production allocation problem in a multi-echelon supply chain with carbon policies. With web-based search engines such as Scopus and Web of Science several resources such as journals, conference proceedings and books are selected and reviewed. It is observed from the literature that the mentioned problem traces the progression of carbon policies in a supply chain over the past 22 years to provide substantiation for Green Supply Chain. The research papers are then analyzed and categorized to construct the useful foundation of previous studies. Moreover, the importance of this problem in recent years needs has been highlighted by mentioning the gaps in the literature. Further, at the end of the paper, several future work directions in this area also suggested.(undefined)info:eu-repo/semantics/publishedVersio

Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain

The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment

Smart Sustainable Manufacturing Systems

With the advent of disruptive digital technologies, companies are facing unprecedented challenges and opportunities. Advanced manufacturing systems are of paramount importance in making key enabling technologies and new products more competitive, affordable, and accessible, as well as for fostering their economic and social impact. The manufacturing industry also serves as an innovator for sustainability since automation coupled with advanced manufacturing technologies have helped manufacturing practices transition into the circular economy. To that end, this Special Issue of the journal Applied Sciences, devoted to the broad field of Smart Sustainable Manufacturing Systems, explores recent research into the concepts, methods, tools, and applications for smart sustainable manufacturing, in order to advance and promote the development of modern and intelligent manufacturing systems. In light of the above, this Special Issue is a collection of the latest research on relevant topics and addresses the current challenging issues associated with the introduction of smart sustainable manufacturing systems. Various topics have been addressed in this Special Issue, which focuses on the design of sustainable production systems and factories; industrial big data analytics and cyberphysical systems; intelligent maintenance approaches and technologies for increased operating life of production systems; zero-defect manufacturing strategies, tools and methods towards online production management; and connected smart factories

Review of mathematical models for production planning under uncertainty due to lack of homogeneity: proposal of a conceptual model

[EN] Lack of homogeneity in the product (LHP) appears in some production processes that confer heterogeneity in the characteristics of the products obtained. Supply chains with this issue have to classify the product in different homogeneous subsets, whose quantity is uncertain during the production planning process. This paper proposes a generic framework for reviewing in a unified way the literature about production planning models dealing with LHP uncertainty. This analysis allows the identification of similarities among sectors to transfer solutions between them and gaps existing in the literature for further research. The results of the review show: (1) sectors affected by LHP inherent uncertainty, (2) the inherent LHP uncertainty types modelled, and (3) the approaches for modelling LHP uncertainty most widely employed. Finally, we suggest a conceptual model reflecting the aspects to be considered when modelling the production planning in sectors with LHP in an uncertain environment.This research was initiated within the framework of the project funded by the Ministerio de Economía y Competitividad [Ref. DPI2011-23597] entitled ‘Methods and models for operations planning and order management in supply chains characterised by uncertainty in production due to the lack of product uniformity’ (PLANGES-FHP) already finished. After, the project leading to this application has received funding from the European Union’s research and innovation programme under the H2020 Marie Skłodowska-Curie Actions with the grant agreement No 691249, Project entitled ’Enhancing and implementing Knowledge based ICT solutions within high Riskand Uncertain Conditions for Agriculture Production Systems’ (RUC-APS).Mundi, I.; Alemany Díaz, MDM.; Poler, R.; Fuertes-Miquel, VS. (2019). 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Aerospace Manufacturing-Remanufacturing System Modeling and Optimization

In recent years, increasing environmental concerns, costs of raw materials, and stricter government regulations have resulted in companies striving to reduce their waste materials. An earlier approach adopted was the recycling of materials such as waste paper, glass and metals. However, recycled products typically lose a portion of their added values. Different waste reduction options such as direct reuse, repair, refurbishing, cannibalization, and remanufacturing were studied to overcome this drawback. Remanufacture recaptures the value added to materials when a product was first manufactured. In the aerospace industry, where safety and performance are the overriding concerns and repairs are highly regulated, it could be perceived that remanufacturing has minimal appeal. However, the very low design tolerance of manufactured components results in a high percentage of defects. Due to the high price of raw materials, remanufacturing and components saving through “transforming” could be applied in imperfect production systems to reduce the amount of scrap materials. In this thesis, a general model is first proposed for a closed-loop supply chain network which includes the following processes: repairs, remanufacturing and transforming of selected defective components and end-of-life products, and cannibalization. A mixed integer linear programming formulation is developed to investigate the effect of various factors on profit, inventory carrying cost, and number of scrap components. Uncertainty in demand and lead-time is one of the major issues in any manufacturing supply chain. Uncertainty is incorporated into an extended model through the scenario-analysis approach and outsourcing is considered as an option for remanufacturing of the customer owned components. Demand of final products is assumed to be deterministic. The defect rate of disassembled components, however, is considered to be variable which makes the demand for spares to be variable. The lead-time of in-house remanufacturing of the customer owned components is also considered to be variable. Sensitivity analysis is performed to investigate the effect of capacity, inventory carrying cost, outsourcing cost, lead-time, and defect rate variation on profit and amount of scraps. The inventory carrying cost variations have direct effect on the inventory turnover ratio. The maximum capacity of the outsourced company and process costs per unit have significant effect on the profitability. Maintaining a long-term relationship with third-party service providers, designing the components with a longer life cycle, and transforming and remanufacturing of defective components directly impact the profitability over the life cycle of a product