Development of Fuzzy Inventory Model under Decreasing Demand and increasing Deterioration Rate

This research study proposed an inventory model with both the time varying variable deterioration and demand rate under the fuzzy environment. Fuzzy set theory is generally consider with imprecision and uncertainty nature of quantitative coefficients. In this system, we assumed the linearly increasing and decreasing function of time  for deterioration and demand respectively. In this research work, we discuss a fuzzy inventory model solving by signed distance method where demand follow time varying.&nbsp

The Impact of Cost Allocation on Key Decisions of Supply Chain Participants

Abstract - Modern business processes are impossible without a logistics system. Logistics costs constitute the lion’s share in the total product cost. The purpose of our research is to study the dependence of decision-making on the level of logistics costs. In order to achieve the goal set, questionnaire, mathematical modeling and analysis methods were used in the study. The main problems of cost management in supply chains were highlighted. In the course of our research, we concluded that a universal solution to the problem can be developed for a limited segment of enterprises, since there is no identical solution to increasing cost efficiency for different types of enterprises. According to the results of the questionnaire, managers’ decisions on increasing efficiency are dependent on their subjective desires rather than dictated by the economic efficiency. Sixty-seven per cent of the respondents are ready to reject a profitable project due to risks. The questionnaire also showed that only 4% of the managers are ready to quit an already implemented project if it is ineffective. This begs the question: do all projects prove to be really effective after their implementation? A two-factor mathematical model with a dummy variable showed the dependence of increased logistics costs on the period in which they were implemented. The mathematical model obtained during the study will be useful for predicting and budgeting the level of logistics costs. It can also encourage independent enterprises to build advanced mathematical models

Fuzzy Modeling Approach to On-Hand Stock Levels Estimation in (R, S) Inventory Systems with Lost Sales

[EN] Purpose: One challenge in inventory control models is to know the stock available at the beginning of the cycle to satisfy future demands, i.e. to know the on-hand stock levels at order delivery. For inventory managers, this knowledge is necessary to both determine service levels and establish the control parameters of the inventory policy. However, the calculation of on-hand stock levels when unfilled demand is lost is mathematically complex since on-hand stock cannot be negative by definition. The purpose of this paper is to propose a new approach to estimate on-hand stock levels when the inventory is periodically reviewed and unfilled demand is lost, through the use of fuzzy techniques. Design/methodology/approach: This paper applies fuzzy set techniques for the calculation of the on-hand stock levels at order delivery in the lost sales context, based on the uncertainty that real demand introduces. To this end, we propose a new approach based on modeling the on-hand stock as an imprecise Markov chain using possibility functions, which reduces significantly the computational effort required to obtain the on-hand stock levels. Findings: To illustrate the performance of the proposed method, two experiments are carried out. The first experiment shows that the proposed fuzzy method correctly calculates on-hand stock levels with insignificant deviation with respect the exact vector. Additionally, the results illustrate that the fuzzy method simplifies the calculation and highly reduces the computational efforts. The second experiment shows the performance of the fuzzy method when it is used to estimate service levels by means of the fill rate. The results show that the proposed method accurately estimates the fill rate with average deviations lower than 0.00015. Practical implications: Knowing the on-hand stock vector is important for inventory managers to establish the control parameters of the system, i.e. to determine the minimum base stock level, S, that guarantees the achievement of a target service level. The difficulty of this estimation is that to obtain the on-hand stock vector in a lost sales context requires a huge computational effort and it is difficult to implement in companies' information systems. However, the proposed fuzzy method leads to a very accurate calculation of the on-hand stock vector significantly reducing the computational costs, which makes this method easily implementable in practical environments. Originality/value: Fuzzy set techniques have been widely used in inventory models to introduce the uncertainty of demand, costs or shortage. However, to the best of our knowledge, this is the first paper which deals directly with fuzzy estimation of on-hand levels.This work was supported by Generalitat Valenciana under the project with reference GV/2017/032.Guijarro, E.; Babiloni, E.; Canós-Darós, MJ.; Canós-Darós, L.; Estelles Miguel, S. (2020). Fuzzy Modeling Approach to On-Hand Stock Levels Estimation in (R, S) Inventory Systems with Lost Sales. Journal of Industrial Engineering and Management. 13(2):464-474. https://doi.org/10.3926/jiem.3071S46447413

A FUZZY GOAL PROGRAMMING APPROACH FOR SOLVING MULTI-OBJECTIVE SUPPLY CHAIN NETWORK PROBLEMS WITH PARETO-DISTRIBUTED RANDOM VARIABLES

Uncertainty is unavoidable and addressing the same is inevitable. That everything is available at our doorstep is due to a well-managed modern global supply chain, which takes place despite its efficiency and effectiveness being threatened by various sources of uncertainty originating from the demand side, supply side, manufacturing process, and planning and control systems. This paper addresses the demand- and supply-rooted uncertainty. In order to cope with uncertainty within the constrained multi-objective supply chain network, this paper develops a fuzzy goal programming methodology, with solution procedures. The probabilistic fuzzy goal multi-objective supply chain network (PFG-MOSCN) problem is thus formulated and then solved by three different approaches, namely, simple additive goal programming approach, weighted goal programming approach, and pre-emptive goal programming approach, to obtain the optimal solution. The proposed work links fuzziness in transportation cost and delivery time with randomness in demand and supply parameters. The results may prove to be important for operational managers in manufacturing units, interested in optimizing transportation costs and delivery time, and implicitly, in optimizing profits. A numerical example is provided to illustrate the proposed model

Efficient near-optimal procedures for some inventory models with backorders-lost sales mixture and controllable lead time, under continuous or periodic review

This paper considers a number of inventory models with backorders-lost sales mixture, stockout costs, and controllable lead time. The lead time is a linear function of the lot size and includes a constant term that is made of several components. These lot-size-independent components are assumed to be controllable. Both single- and double-echelon inventory systems, under periodic or continuous review, are considered. To authors knowledge, these models have never been previously studied in literature. The purpose of this paper is to analyse and optimize these novel inventory models. The optimization is carried out by means of heuristics that work on an ad hoc approximation of the cost functions. This peculiarity permits to exploit closed-form expressions that make the optimization procedure simpler and more readily applicable in practice than standard approaches. Finally, numerical experiments investigate the efficiency of the proposed heuristics and the sensitivity of the developed models

Distribution-free approach for stochastic joint-replenishment problem with backorders-lost sales mixtures, and controllable major ordering cost and lead times

In this paper, we study the periodic-review Joint-Replenishment Problem (JRP) with stochastic demands and backorders-lost sales mixtures. We assume that lead times aare made of two major components: a common part to all items and an item-specific portion. We further suppose that the item-specific component of lead times and the major ordering cost are controllable. To reflect the practical circumstance characterized by the lack of complete information about the demand distribution, we adopt the minimax distribution-free approach. That is, we assume that only the mean and the variance of the demand can be evaluated. The objective is to determine the strict cyclic replenishment policy, the length of (the item-specific component of) lead times, and the major ordering cost that minimize the long-run expected total cost. To approach this minimization problem, we present a first optimization algorithm. However, numerical tests highlighted how computationally expensive this algorithm would be for a practical application. Therefore, we then propose two alternative heuristics. Extensive numerical experiments have been carried out to investigate the performance of the developed algorithms. Results have shown that the proposed alternative heuristics are actually efficient and seem therefore promising for a practical application

Coordenação e desenvolvimento da operação logística

Na atualidade, não só o mercado está a tonar-se cada vez mais desenvolvido e consequentemente mais exigente e competitivo, como também, os consumidores têm à sua disposição muita mais informação. Isto requer da parte das empresas, a necessidade de reduzir custos e desperdícios de forma a possuírem preços competitivos, sendo um desses custos, os transportes, uma vez que uma boa gestão de transportes/distribuição pode levar a um aumento das margens de lucro. O presente trabalho foi desenvolvido na empresa Skk - Central de Distribuição Para Refrigeração e Climatização, S.A, em Matosinhos. Teve como principal objetivo sugerir/implementar método ou ferramenta que permita otimizar a distribuição de material dos fornecedores para os três armazéns (Porto, Lisboa e Coimbra), bem como a distribuição do material entre os mesmos. Desta forma, foram apresentadas duas propostas de melhoria, uma formação com o objetivo de conhecer todas as funcionalidades do software usado e o desenvolvimento de um modelo matemático de modo a otimizar a distribuição do material dos fornecedores para os armazéns, tendo em consideração as diferentes características de todas as entidades envolventes. Com a formação, foi possível perceber que o software utilizado pela empresa tem bastantes limitações e, portanto, a melhor solução encontrada foi a sua substituição. Quanto ao modelo, desenvolvido no programa CPLEX, obtiveram-se como resultados para os artigos estudados, que 71% das necessidades foram satisfeitas diretamente através dos fornecedores, 23% via transshipment pelo armazém do Porto, 5% via transshipment pelo armazém de Lisboa e 1% via transshipment pelo armazém de Coimbra.Currently, not only is the market becoming increasingly more developed and consequently more demanding and competitive, but also consumers have at their disposal much more information. This requires companies the need to reduce costs and waste to have competitive prices, and one of these costs being transport, since a good transport/distribution management can lead to an increase in profit margins. The present work was developed at the company Skk - Central de Distribuição Para Refrigeração e Climatização, S.A, in Matosinhos. It´s main objective was to suggest/implement a method or a tool that allows optimizing the distribution of material from suppliers to the three warehouses (Porto, Lisboa and Coimbra), as well the distribution of material between them. In this way, two improvment proposoals were made, a training course with the objective of knowing all the features of the software usde and the development of a mathematical model in order to optimize the distribution of material from the suplliers to the warehouses, taking into consideration the different characteristics of all the surrounding entities. With the training course, it was possible to understand that the software used by the company has many limitations and, therefore, the best solution found was to replace it. Regarding the model, developed in the CPLEX program, the results for the items studied were that 71% of the needs were fulfilled directly through suplliers, 23% via transshipment by the warehouse in Porto, 5% via transshipment by tha warehouse in Lisboa and 1% via transshipment by the warehouse in Coimbra

Propuesta de gestión de inventarios para mejorar el proceso de abastecimiento, mediante desarrollo de pronósticos y el sistema de revisión periódica en una empresa comercializadora de lubricantes

En el mercado actual, existe una gran cantidad de pymes comerciales que presentan un amplio margen de pérdidas económicas por quiebres de stock, debido al ineficiente proceso de abastecimiento. En otras palabras, las ventas perdidas y los costos adicionales generados al no tener sus productos disponibles en sus almacenes es un escenario crítico en empresas distribuidoras, cuyo valor agregado radica en maximizar su nivel de servicio al cliente. Para resolver este problema, proponemos un sistema que integra el desarrollo de pronósticos y el modelo de inventarios de revisión periódica, ambas herramientas basadas en el marco de trabajo que se plantea teniendo en cuenta modelos de gestión del conocimiento. Los pronósticos realizados, luego de analizar la demanda, sus patrones y elegir el mejor método a utilizar, son antecedentes para desarrollar la gestión de inventarios y sus políticas. Asimismo, la gestión del conocimiento actuará como soporte del sistema integrado al asegurar que el conocimiento adquirido sea sostenible y se mantenga en el tiempo hasta ser renovado. A través de la simulación realizada para nuestro caso de estudio GP Maquinarias S.A.C., una pyme distribuidora de lubricantes, se obtuvieron resultados que indican una reducción del 93% en las pérdidas por desabastecimientos y un aumento del nivel de servicio que pasa de 79% a 91%. Esta propuesta constituye un sistema integrado interesante para ser aplicado como solución para pymes que presentan altos índices de desabastecimiento y carezcan de este tipo de herramientas.In the current market, there is a large number of SMEs that have a large margin of economic losses due to lack of stocks, due to the supply process. In other words, the lost sales and the costs of the services generated by not having their products available in their warehouses is a critical scenario in the distribution companies, whose added value lies in maximizing their level of customer service. To solve this problem, we propose a system that integrates the development of the attention and the model of the inventories of the periodic review, the bases based on the framework of the work. The results, after analyzing the demand, their patterns and choosing the best method to use, are antecedents to develop the management of inventories and their policies. Likewise, knowledge management will act as an integrated support. Through the simulation carried out for our study case GP Maquinarias S.A.C., a SMEs distributor of lubricants, results were obtained that indicate a reduction of 93% in losses due to stock-outs and an increase in the service level that goes from 79% to 91%. This is an integrated system of interest to be applied as a solution for SMEs that have high stock-outs and lack this type of tools.Trabajo de Suficiencia Profesiona

The impact of adopting Additive Manufacturing on responsive supply chain performance

Additive Manufacturing (AM), or 3D printing as it is frequently known, is an umbrella term for a collection of manufacturing technologies that enables products to be manufactured layer-by-layer from three-dimensional digital data. While the costs associated with AM represents a barrier to its wider adoption, its benefits outweigh its costs when considered in some contexts. Few studies have investigated the costs and benefits of this technology from a supply chain perspective, particularly in market environments characterized by demand uncertainty. In this type of scenario, it becomes necessary to adopt higher levels of internal competencies, find the optimal way to manage inventories and flexibly respond to sudden market requirements. This thesis therefore aims to address this gap by examining three key aspects: the learning effects offered by AM, the impact of AM on inventory-related costs and the impact of AM on the critical capability of flexibility. To assess learning in AM, this thesis focuses on the experimental measurement of AM operator time and improvement in operator effectiveness as a result of learning. Learning is thus assessed by measuring the reduction of labour time through operator learning within a series of build repetitions and estimates a progress ratio which captures the learning effect within this series. To assess the impact of AM on inventory-related costs, this thesis develops a conceptual model that matches possible AM scenarios with demand volume level and severity of stockout penalty. It also conducts a case study to obtain insights into the resulting model which has been developed. In this case study, an interprocess comparison is undertaken by simulating a supply chain based on data collected from a plastic products manufacturing company that produces pipe fittings using Injection Moulding (IM) technology. The simulation model produced has been built using the Arena software package for three distinct scenarios: the current configuration with IM only, iii a proposed configuration with AM only, and a proposed configuration that combines AM with IM. To evaluate the impact of AM on flexibility, a conceptual model has also been constructed that maps certain AM characteristics relevant to flexibility to key market disruption scenarios faced by managers. This aspect is also highlighted through the case study which assesses the impact of AM on four distinct supply chain flexibility types: volume, delivery, mix and new product using metrics obtained from the literature. The results obtained on learning in AM suggest that AM exhibits a learning effect for both the novice and the expert operator with progress ratios of 67.73% and 80.42% respectively. Further, results on the impact of AM on inventory-related costs revealed that utilizing IM alone showed the lowest supply chain unit cost (€0.90) compared to utilizing AM as a stand-alone (€2.72) or in a combined approach (€0.94). With regards to AM’s impact on flexibility, the supply chain employing IM showed greater volume and delivery flexibility levels (i.e. 65.68% and 92.8% for IM compared to 58.70% and 75.35% for AM, respectively). However, AM showed higher mix and new product introduction flexibility level, indicated by the lower changeover time and cost of new product introduction to the system (i.e. 0.33 hrs and €0 for AM compared to 4.91 hrs and €30,000 for IM, respectively). It is anticipated that these results can be used to inform practitioners and scholars on various contexts where AM can create value and the appropriate and timely investments needed to unlock that value