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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Reverse logistics

This paper gives an overview of scientific literature that describes and discusses cases of reverse logistics activities in practice. Over sixty case studies are considered. Based on these studies we are able to indicate critical factors for the practice of reverse logistics. In addition we compare practice with theoretical models and point out research opportunities in the field

A supply chain model under return policy considering refurbishment, learning effect and inspection error

This article presents a three-echelon supply chain model consisting of a supplier, manufacturer, and a retailer, considering the return contract between the manufacturer and the retailer. Here, the manufacturer has two adjacent production units - the main production unit and a refurbishment unit. The main production unit of the manufacturer is imperfect, which produces an admixture of perfect and defective items. He inspects all the products immediately after production and sells good quality items to the retailer. The retailer receives a proportion of faulty products from him due to his erroneous inspection process, which he returns after inspection. The manufacturer sends all the defective products received from the retailer and the main production unit to the refurbishment unit for reworking. Moreover, the learning effect of the employees on the production cost is considered. Under these circumstances, the cost functions of each of the supply chain players have been derived. Finally, the applicability of the proposed model has been shown using a numerical example. The sensitivity analysis has been presented to study the effect of the parameters on the optimum decision variables

Integrating Closed-loop Supply Chains and Spare Parts Management at IBM

Ever more companies are recognizing the benefits of closed-loop supplychains that integrate product returns into business operations. IBMhas been among the pioneers seeking to unlock the value dormant inthese resources. We report on a project exploiting product returns asa source of spare parts. Key decisions include the choice of recoveryopportunities to use, the channel design, and the coordination ofalternative supply sources. We developed an analytic inventory controlmodel and a simulation model to address these issues. Our results showthat procurement cost savings largely outweigh reverse logistics costsand that information management is key to an efficient solution. Ourrecommendations provide a basis for significantly expanding the usageof the novel parts supply source, which allows for cutting procurementcosts.supply chain management;reverse logistics;product recovery;inventory management;service management

A Fuzzy Two-warehouse Inventory Model for Single Deteriorating Item with Selling-Price-Dependent Demand and Shortage under Partial-Backlogged condition

In this paper we have developed an inventory model for a single deteriorating item with two separate storage facilities (one is owned warehouse (OW) and the other a rented warehouse (RW)) and in which demand is selling- price dependent. Shortage is allowed and is partially backlogged with a rate dependent on the duration of waiting time up to the arrival of next lot. It is assumed that the holding cost of the rented warehouse is higher than that of owned warehouse. As demand, selling- price, holding- cost, shortage, lost- sale, deterioration- rate are uncertain in nature, we consider them as triangular fuzzy numbers and developed the model for fuzzy total cost function and is defuzzified by using Signed Distance and Centroid methods. In order to validate the proposed model, we compare the results of crisp and fuzzy models through a numerical example and based on the example the effect of different parameters have been rigorously studied by sensitivity analysis taking one parameter at a time keeping the other parameters unchanged

Integrating Closed-loop Supply Chains and Spare Parts Management at IBM

Ever more companies are recognizing the benefits of closed-loop supply chains that integrate product returns into business operations. IBM has been among the pioneers seeking to unlock the value dormant in these resources. We report on a project exploiting product returns as a source of spare parts. Key decisions include the choice of recovery opportunities to use, the channel design, and the coordination of alternative supply sources. We developed an analytic inventory control model and a simulation model to address these issues. Our results show that procurement cost savings largely outweigh reverse logistics costs and that information management is key to an efficient solution. Our recommendations provide a basis for significantly expanding the usage of the novel parts supply source, which allows for cutting procurement costs

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

Inventory Models for Manufacturing Process with Reverse Supply Chain

Technology innovation leading to development of new products and enhancement of features in existing products is happening at a faster pace than ever. This trend has resulted in gross increase in use of new materials and decreased customers‘ interest in relatively older products leading to the deteriorating conditions of the environment due to the reduction of non-renewable resources and steady increase in the land fill of waste. This has forced organizations and communities to consider recovery alternatives such as reuse, repair, recycle, refurbish, remanufacture and cannibalize, rather than discarding of the products after end of life. Products are retuned back or become redundant because either they do not function properly or functionally they become obsolete. The sources of these returns are Manufacturing returns, Distribution returns and Customer returns. The product recovery options in reverse supply are Repair, Refurbish, Re-manufacture, Cannibalize and Recycle. The main difference between the options is in the reprocessing techniques. Where Repair, refurbishing, and remanufacturing are involved in the up gradation of the used products in quality and/or technology with a difference with respect to the degree of up gradation(repair involves the least, and remanufacturing the largest),the cannibalization and recycling are involved in using parts ,components and materials of the used products. Although much is being disused on the different recovery options still a lot of research remains to be done for improvement of the currently available techniques. In this context the present work focuses on remanufacturing option of recovery process for return items which is the most advanced and environmentally friendly production processes in use. Therefore the broad objectives of the present work are to deal with the different models of remanufacturing either new or existing for adding new features to it and making it simple and more user oriented, to develop deterministic models using direct manufacturing and remanufacturing for profit optimization, to develop and deal with probabilistic models of inventory with demand fluctuation using direct manufacturing and remanufacturing.to select and recommend a tool for predicting various critical parameters associated with the Reverse supply chain (RSC).to make these models usable to achieve maximum advantages by reutilization of resources integrating the upstream and downstream chains. For the effective implementation of remanufacturing in Reverse supply chain, the entire work has been arranged in different chapters to present the distinct aspects of the research. Models are developed with special reference to remanufacturing. These models proposed helped in minimizing the gaps existing in the RSC in the v present scenario. The different models proposed for RSC are discussed on the basis of deterministic and probabilistic approaches. Although a lot of assumptions are intentionally made to make the models deterministic, still these models have its own identity in satisfying the needs of RSC. Two models are being discussed under deterministic approach. These models tries to find out the amount of new product supply to the market, the amount of remanufactured products supply to the market, the amount of products returned from the market and the amount of waste. Pertinent data from industry have been considered to prepare the models. The model variables are tested with adaptive-network-based fuzzy inference system (ANFIS), where the testing of the actual out come and desired outcome is done by using ANFIS. One of the proposed models is picked up to predict the critical parameters associated with RSC using remanufacturing. Although the models dealing with the deterministic RSC models are simple still it becomes difficult to deal with a situation where there is a fluctuation of demand in the market, which is a common phenomenon. Therefore, it becomes inevitable to use the probabilistic approach for sorting out it. The aim is to deal with probabilistic models of inventory and models are proposed where the uncertainty due to fluctuation of demand and uncertainty in the return rate of used products is taken care of by using the safety stock. The determination of the safety stock is done on the basis of service level approach. The model variables are optimized using mathematical models considering the profit maximization. The contribution of the present work is directed towards the environmental benefits. The manufacture of durable goods is one of the major contributors to the GNP of all developed countries. It employs large amounts of human resources, raw materials and energy. The raw materials and energy in the production of durable goods have been continually depleted. Many durable products are disposed in landfills at the end of their useful lives as well. The landfill space has been decreasing and the price charged by the landfills is increasing at a faster rate. This becomes an environmental concern. Remanufacturing, as discussed earlier is one of the predominant product recovery option for the return products. With respect to quality it is considered to be as good as new ones but with a lower cost of conversion. Therefore, focusing on remanufacturing option of product recovery not only decreases the depletion rate of virgin raw materials and rate of land fill but also contributes much towards the GDP as well as GNP. The models proposed in this work are simple and can be practically implemented to get benefits from the return items and still satisfying the market demand for sustainable production

Modelling of Coordinating Production and Inventory Cycles in A Manufacturing Supply Chain Involving Reverse Logistics

In today’s global and competitive markets selling products at competitive prices, coordination of supply chain configuration, and environmental and ecological consciousness and responsibility become important issues for all companies around the world. The price of products is affected by costs, one of which is inventory cost. Inventory does not give any added value to products but must be kept in order to fulfill the customer demand in time. Therefore, this cost must be kept at the minimum level. In order to reduce the amount of inventory across a supply chain, coordination of decisions among all players in the chain is necessary. Coordination is needed not only for a two-level supply chain involving a manufacturer and its customers, but also for a complex supply chain of multiple tiers involving many players. With increasing attention being placed to environmental and ecological consciousness and responsibility, companies are keen to have a reverse supply chain where used products are collected and usable components remanufactured and reused in production to minimize negative impacts on the environment, adding further complexity to decision making across a supply chain. To deal with the above issues, this thesis proposes and develops the mathematical models and solution methods for coordinating the production inventory system in a complex manufacturing supply chain involving reverse logistics and multiple products. The supply chain consists of tier-2 suppliers for raw materials, tier-1 suppliers for parts, a manufacturer who manufactures and assembles parts into finished products, distributors, retailers and a third party who collects the used products and returns usable parts to the system. The models consider a limited contract period among all players, capacity constraints in transportation units and stochastic demand. The solution methods for solving the models are proposed based on decentralized, semi-centralized and centralized decision making processes. Numerical examples are used by adopting data from the literature to demonstrate, test, analyse and discuss the models. The results show that centralised decision making process is the best way to coordinate all players in the supply chain which minimise total cost of the supply chain as a whole. The results also show that the selection of the length of limited horizon/ contract period will be one of the main factors which will determine the type of coordination (decentralised, centralised or semi-centralised) among all players in the supply chain. We also found that the models developed can be viewed as generalised models for multi-level supply chain by examining the models using systems of different tiers from the literature. We conclude that the models are insensitive to changes of input parameters since percentage changes of the supply chain’s total cost are less than percentage changes of input parameters for the scenarios studied