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

Sustainable Inventory Management Model for High-Volume Material with Limited Storage Space under Stochastic Demand and Supply

Inventory management and control has become an important management function, which is vital in ensuring the efficiency and profitability of a company’s operations. Hence, several research studies attempted to develop models to be used to minimise the quantities of excess inventory, in order to reduce their associated costs without compromising both operational efficiency and customers’ needs. The Economic Order Quantity (EOQ) model is one of the most used of these models; however, this model has a number of limiting assumptions, which led to the development of a number of extensions for this model to increase its applicability to the modern-day business environment. Therefore, in this research study, a sustainable inventory management model is developed based on the EOQ concept to optimise the ordering and storage of large-volume inventory, which deteriorates over time, with limited storage space, such as steel, under stochastic demand, supply and backorders. Two control systems were developed and tested in this research study in order to select the most robust system: an open-loop system, based on direct control through which five different time series for each stochastic variable were generated, before an attempt to optimise the average profit was conducted; and a closed-loop system, which uses a neural network, depicting the different business and economic conditions associated with the steel manufacturing industry, to generate the optimal control parameters for each week across the entire planning horizon. A sensitivity analysis proved that the closed-loop neural network control system was more accurate in depicting real-life business conditions, and more robust in optimising the inventory management process for a large-volume, deteriorating item. Moreover, due to its advantages over other techniques, a meta-heuristic Particle Swarm Optimisation (PSO) algorithm was used to solve this model. This model is implemented throughout the research in the case of a steel manufacturing factory under different operational and extreme economic scenarios. As a result of the case study, the developed model proved its robustness and accuracy in managing the inventory of such a unique industry

Strategic opportunities for product-agnostic remanufacturing

Purpose There is now much emphasis in both research and practice on the principles of circular economies. In this paper remanufacturing is examined as a key enabler of circular practices, and the concept of “Product-Agnostic Manufacturing” (PAR) is proposed. This work differentiates PAR from many traditional approaches to remanufacturing by virtue of PAR's treatment of product variety. Most existing approaches to remanufacturing feature low variety and standardisation; this study instead suggests that the exploitation of flexibilities in both operations and supply chains leads to new competitive strategies for firms to exploit. Design/methodology/approach This is a conceptual study that builds on a thorough exploration of contemporary remanufacturing literature in the development of the new PAR concept. Findings Through a detailed literature review it is shown that there are a range of benefits, challenges, and critical success factors that underpin the remanufacturing concept. Building on this understanding and bridging literature in operations flexibility and supply chain design, a detailed discussion on the nature of PAR is provided, and an agenda for future research developed. Originality/value Whilst there has been much literature on remanufacturing, there is a general tendency to treat supply chain and remanufacturing operations quite distinctly in individual articles. Additionally, there has been little consideration of multi-product remanufacturing, and for the limited studies where this is done, the emphasis is typically on problem avoidance. This study aims to provide a detailed insight into the developed PAR concept, showing how the remanufacture of a wide range of product varieties may be achieved through flexible operations and supply chain design

Manufacturing Value Modelling, Flexibility, and Sustainability: from theoretical definition to empirical validation

The aim of this PhD thesis is to investigate the relevance of flexibility and sustainability within the smart manufacturing environment and understand if they could be adopted as emerging competitive dimensions and help firms to take decisions and delivering value

Supply chain inventory control for the iron and steel industry

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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

A review of discrete-time optimization models for tactical production planning

This is an Accepted Manuscript of an article published in International Journal of Production Research on 27 Mar 2014, available online: http://doi.org/10.1080/00207543.2014.899721[EN] This study presents a review of optimization models for tactical production planning. The objective of this research is to identify streams and future research directions in this field based on the different classification criteria proposed. The major findings indicate that: (1) the most popular production-planning area is master production scheduling with a big-bucket time-type period; (2) most of the considered limited resources correspond to productive resources and, to a lesser extent, to inventory capacities; (3) the consideration of backlogs, set-up times, parallel machines, overtime capacities and network-type multisite configuration stand out in terms of extensions; (4) the most widely used modelling approach is linear/integer/mixed integer linear programming solved with exact algorithms, such as branch-and-bound, in commercial MIP solvers; (5) CPLEX, C and its variants and Lindo/Lingo are the most popular development tools among solvers, programming languages and modelling languages, respectively; (6) most works perform numerical experiments with random created instances, while a small number of works were validated by real-world data from industrial firms, of which the most popular are sawmills, wood and furniture, automobile and semiconductors and electronic devices.This study has been funded by the Universitat Politècnica de València projects: ‘Material Requirement Planning Fourth Generation (MRPIV)’ (Ref. PAID-05-12) and ‘Quantitative Models for the Design of Socially Responsible Supply Chains under Uncertainty Conditions. Application of Solution Strategies based on Hybrid Metaheuristics’ (PAID-06-12).Díaz-Madroñero Boluda, FM.; Mula, J.; Peidro Payá, D. (2014). A review of discrete-time optimization models for tactical production planning. International Journal of Production Research. 52(17):5171-5205. doi:10.1080/00207543.2014.899721S51715205521

Robotix-Academy Conference for Industrial Robotics (RACIR) 2019

Robotix-Academy Conference for Industrial Robotics (RACIR) is held in University of Liège, Belgium, during June 05, 2019. The topics concerned by RACIR are: robot design, robot kinematics/dynamics/control, system integration, sensor/ actuator networks, distributed and cloud robotics, bio-inspired systems, service robots, robotics in automation, biomedical applications, autonomous vehicles (land, sea and air), robot perception, manipulation with multi-finger hands, micro/nano systems, sensor information, robot vision, multimodal interface and human-robot interaction.

Készletmodellek a visszutas logisztikában = Inventory Models in Reverse Logistics

A visszutas logisztika (reverse logistics) a vállalati logisztika szemszögéből a logisztika azon szerepére utal, amely a termékek visszatérésében, a felhasznált erőforrások csökkentésében, recyclingban, anyagok helyettesítésében, anyagok újrafelhasználásában, hulladékkezelésben, valamint feljavításban, javításban és újrafeldolgozásban nyilvánul meg. A logisztika technikai szemszögéből a visszutas logisztikai menedzsment arra vonatkozik, hogy egy olyan szisztematikus vállalati modellt hozzon létre, amely a legjobb logisztikai menedzsment technikákat alkalmazza a vállalatban azért, hogy nyereségesen zárja az ellátási láncot. Az ellátási lánc zárása azt jelenti, hogy nem csak a logisztika hagyományos definícióját tekintjük, azaz a beszállító-termelő-fogyasztó irányú anyagáramlást, hanem ebbe a láncba integrálva a használt anyagok fogyasztó-termelő-beszállító irányú visszafelé áramlását is. A visszutas logisztikának ebben a felfogásban környezetvédelmi és menedzsment vonzatai is vannak. A fogyasztás-felhasználás szférájából visszaáramló anyagok újrafeldolgozása és –felhasználása csökkenti az elsődleges természeti erőforrások kitermelését, de a természeti környezet használt anyagokkal történő terhelését is. Ezzel a logisztikának ez az ága tevőlegesen hozzájárulhat a fenntarható fejlődéshez. A vállalati menedzsment szempontjából vállalati erőforrások takaríthatóak meg azzal, hogy (pl. garanciális hiba miatt) vissszaküldött, de még újrafeldolgozható termékek javítás, vagy újrafeldolgozás utáni piacra dobásával tőkét takaríthat meg a vállalat. Mindent összevetve az újrafelhasználás, mint jelenség nem újkeletű. Pl. papírgyűjtés és újrafelhasználás mindig is létezett. Ami a visszutas logisztika újszerűségében rejlik az az, hogy mindezt a vállalati gazdálkodás stratégiájába próbálja beilleszteni. Jelen tanulmányban a visszutas logisztika általam ismert determinisztikus egytermékes készletmodelljeit bemutatja be. Először a Schrady-féle javítási modellt mutatom be (Schrady (1967)), amelyet a dolgozat szerzője általánosított több beszerzési tétel esetére. (Dobos (2002)) A következő modell Schrady modelljének Nahmias és Rivera (1979) által történő általánosítása arra az esetre, amikor az új termékeket a vállalat maga állítja elő, így az új termékek raktárába a beáramlás folytonos. Harmadikként Koh, Hwang, Sohn és Ko, C.-S. (2002) modelljét ismertetem, amely az előző modell egy változatának tekinthető. Ez a három modell kizárólag a tételnagysághoz kapcsolódó költségek minimalizálását tűzi ki célul. A problémák nem foglalkoznak expliciten a hulladékkezelés problémájával, a második modellt kivéve. A másik három modellben az optimális tételnagyságon kívül a fentebb említett lineáris költségeket is tartalmazza. Ebben a csoportban Richter (1996) modelljét tárgyaljom először. Ez a modell az egyetlen három raktáras modell és egy üzemen belüli újrafelhasználási problémát modellez. A következő modell Teunter (2001) dolgozatára alapozódik. Végül, Dobos és Richter (2004) cikke egy olyan szituációt modellez, amikor a használt termékeket a vállalat visszavásárolhatja. E három modellben az optimális termelési és újrafelhasználási tételnagyságokon kívül azt is meg kell határozni, hogy mekkora részét használja újra a vállalat a visszatérő termékeknek és mekkora részét kell hulladékként kezelni. A visszutas logisztika az anyagszükséglet tervezési rendszerekbe (MRP) teljes mértékig integrálható. Az adattábla utolsó sora mutatja a megelőző fázisok és/vagy beszerzés szükségletét e rendszerben. A tábla ezen utolsó sorában jelenik meg a készletgazdálkodási probléma: összevonjon-e a döntéshozó termelési és/vagy beszerzési tételeket. A klasszikus MRP-ben a szükségletek kielégítésére heurisztikákat alkalmaznak, mint a Groff-algoritmus, Silver-Meal-heurisztika stb. Az ilyen heurisztikák szinte minden esetben az optimális tételnagyság modell (EOQ) optimalitási kritériumát használják fel. Ez az a tulajdonság, hogy az optimumban a rendelési/átállítási költségek megegyeznek a készlettartási költségekkel. A kérdés most úgy hangzik, hogy a létező EOQ-típusú visszutas logisztikai modellek hogyan alkalmazhatóak az MRP-ben, mint tételnagyságot meghatároz