An optimal EOQ model for perishable products with varying demand pattern

The demand pattern for most perishable products varies during their life cycle in the market. These variations must be properly reflected in inventory management in order to prevent unnecessary stock-out or excess inventory with associated increase in cost. In this paper, a multi-period economic order quantity (EOQ) model for managing the inventory of perishable items having varying demand pattern is presented. The model was formulated using a general ramp-type demand function that allows three-phase variation in demand pattern. These phases represent the growth, the steady and the decline phases commonly experienced by the demand for most products during their life cycle in the market. The model generates replenishment policies that guarantees optimal inventory cost for all the phases. Numerical experiments and sensitivity analysis were carried out to demonstrate the suitability of the model for a wide range of seasonal products. Result of the experiments revealed that the points at which demand pattern changes are critical points in managing inventory of products with ramp type demand

A Fuzzy Economic Order Quantity (EOQ) Model with Consideration of Quality Items, Inspection Errors and Sales Return

In this paper, we develop an economic order quantity model with imperfect quality, inspection errors and sales returns, where upon the arrival of order lot, 100% screening process is performed and the items of imperfect quality are sold as a single batch at a lessen price, prior to receiving the next shipment. The screening process to remove the defective items may involve two types of errors. In this article we extend the Khan et al. (2011) model by considering demand and defective rate in fuzzy sense and also sales return in our model. The objective is to determine the optimal order lot size to maximize the total profit. We use the signed distance, a ranking method for fuzzy numbers, to find the approximate of total profit per unit time in the fuzzy sense. The impact of fuzziness of fraction of defectives and demand rate on optimal solution is showed by numerical example

A Modified Reverse Supply Chain with Remanufacturing for Sustainable Product Cycle

This paper deals with a new model, in which the stationary demand for a product can be fulfilled by remanufactured products along with newly procured product leading to minimum consumption of virgin raw materials. The remanufactured products are assumed to be as good as new ones and the returned items from the customers can be remanufactured at a fixed rate. The model helps in maintaining the goodwill of the customers by not allowing frequent stock outs by providing safety stock. A model is proposed and analyzed depending on the relationship between different parameters. An interpretive modelling based approach has been employed to model the reverse logistics variables typically found in reverse supply chains. A methodology is used for the calculation of optimum level for the newly manufactured items and the optimum level of the returned items for remanufacturing simultaneously. The major objective is to minimize the waste and gain the competitive advantage of cost of conversion. Moreover the company can sustain in the same line of business for a longer period of time. Keywords Product recovery, remanufacturing, reverse supply chain, sustainable product

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

Modelo de apoio à decisão para a manutenção condicionada de equipamentos produtivos

Doctoral Thesis for PhD degree in Industrial and Systems EngineeringIntroduction: This thesis describes a methodology to combine Bayesian control chart and CBM (Condition-Based Maintenance) for developing a new integrated model. In maintenance management, it is a challenging task for decision-maker to conduct an appropriate and accurate decision. Proper and well-performed CBM models are beneficial for maintenance decision making. The integration of Bayesian control chart and CBM is considered as an intelligent model and a suitable strategy for forecasting items failures as well as allow providing an effectiveness maintenance cost. CBM models provides lower inventory costs for spare parts, reduces unplanned outage, and minimize the risk of catastrophic failure, avoiding high penalties associated with losses of production or delays, increasing availability. However, CBM models need new aspects and the integration of new type of information in maintenance modeling that can improve the results. Objective: The thesis aims to develop a new methodology based on Bayesian control chart for predicting failures of item incorporating simultaneously two types of data: key quality control measurement and equipment condition parameters. In other words, the project research questions are directed to give the lower maintenance costs for real process control. Method: The mathematical approach carried out in this study for developing an optimal Condition Based Maintenance policy included the Weibull analysis for verifying the Markov property, Delay time concept used for deterioration modeling and PSO and Monte Carlo simulation. These models are used for finding the upper control limit and the interval monitoring that minimizes the (maintenance) cost function. Result: The main contribution of this thesis is that the proposed model performs better than previous models in which the hypothesis of using simultaneously data about condition equipment parameters and quality control measurements improve the effectiveness of integrated model Bayesian control chart for Condition Based Maintenance.Introdução: Esta tese descreve uma metodologia para combinar Bayesian control chart e CBM (Condition- Based Maintenance) para desenvolver um novo modelo integrado. Na gestão da manutenção, é importante que o decisor possa tomar decisões apropriadas e corretas. Modelos CBM bem concebidos serão muito benéficos nas tomadas de decisão sobre manutenção. A integração dos gráficos de controlo Bayesian e CBM é considerada um modelo inteligente e uma estratégica adequada para prever as falhas de componentes bem como produzir um controlo de custos de manutenção. Os modelos CBM conseguem definir custos de inventário mais baixos para as partes de substituição, reduzem interrupções não planeadas e minimizam o risco de falhas catastróficas, evitando elevadas penalizações associadas a perdas de produção ou atrasos, aumentando a disponibilidade. Contudo, os modelos CBM precisam de alterações e a integração de novos tipos de informação na modelação de manutenção que permitam melhorar os resultados.Objetivos: Esta tese pretende desenvolver uma nova metodologia baseada Bayesian control chart para prever as falhas de partes, incorporando dois tipos de dados: medições-chave de controlo de qualidade e parâmetros de condição do equipamento. Por outras palavras, as questões de investigação são direcionadas para diminuir custos de manutenção no processo de controlo.Métodos: Os modelos matemáticos implementados neste estudo para desenvolver uma política ótima de CBM incluíram a análise de Weibull para verificação da propriedade de Markov, conceito de atraso de tempo para a modelação da deterioração, PSO e simulação de Monte Carlo. Estes modelos são usados para encontrar o limite superior de controlo e o intervalo de monotorização para minimizar a função de custos de manutenção.Resultados: A principal contribuição desta tese é que o modelo proposto melhora os resultados dos modelos anteriores, baseando-se na hipótese de que, usando simultaneamente dados dos parâmetros dos equipamentos e medições de controlo de qualidade. Assim obtém-se uma melhoria a eficácia do modelo integrado de Bayesian control chart para a manutenção condicionada

Optimizing the economic information transparency level of high-tech enterprises in the post-industrial globalized economy

Purpose: Managerial conditions of economic operation of a high technology enterprise as it integrates into the global economy that is essentially postindustrial and globalized were considered in this article. Design/Methodology/Approach: An inevitable immersion of the enterprise into the well-developed external infosphere, as well as a membrane borderline between the external and the internal infospheres were shown. The enterprise was represented dually – as both a donor and a recipient of information resources. Findings: An interpretation of the content of the infosphere was presented. Multiple causes of the discrete nature of the enterprise’s infosphere implementation were shown. The concept of “informational economic transparency” of an enterprise was introduced, and multiple components determining transparency levels were described. Practical Implications: The influence of transformations of informational economic transparency of an enterprise on external impacts on it from legal relations parties. Positive and negative effect of increases and decreases in the informational economic transparency of the enterprise were highlighted in the context of its influence on the economic counterpart and conflict-studies situations. The understanding of the specialized control object was provided. The optimizability of a level of the transparency in the aspect of target orientation of the enterprise was demonstrated. Originality/Value: A structural prototype to the primary support managerial toolkit in the shape of a DSS, a recommender system, allowing to conduct required feasibility studies of managerial decisions was proposed.peer-reviewe

Disparities in empirical welfare measures: the effects of time and information

In a static setting, willingness to pay (WTP) for an increase in quantity or quality is simply equal to the compensating variation, a Hicksian welfare measure. Likewise, willingness to accept compensation in exchange (WTA) for a decrease in quantity or quality is equal to the equivalent variation. However, in a dynamic setting characterized by uncertainty, limited delay or reversal, and the potential for learning, these stated preference measures may also contain option values. Zhao and Kling (Economics Letters , 2001) use real options theory to explain the relationship between learning, irreversibility, and value formulation in a dynamic setting. In this dissertation, I discuss the design and results of two empirical tests of whether stated preference value measures are affected by dynamic aspects of the market environment, and whether those effects, if they exist, are consistent with Zhao and Kling\u27s predictions.;The first test incorporates the dynamic nature of the value formulation process into a contingent valuation study designed to measure the value local residents place on a north-central Iowa lake. My results show that WTP is highly sensitive to the potential for future learning. Respondents offered the opportunity to delay their purchasing decisions until more information became available were willing to pay significantly less for improved water quality than those facing a now-or-never decision. These results suggest that welfare analysts should take care to accurately represent the potential for future learning.;The second test also deals with the effects of learning and irreversibility on stated preference measures, but this time in an experimental economic setting. I test whether part of the disparity observed between WTA and WTP in the experimental economic literature can be explained by the presence of real options. To do this, I have performed a series of experimental treatments designed to analyze the effect subjects\u27 perceptions regarding the relative difficulty of reversal and delay have on their valuation of a private good. While I find some evidence that subjects do take into account dynamic considerations, I cannot show that WTA and WTP are affected in a manner consistent with Zhao and Kling\u27s theory

Inventory Control Model of Beef for Rendang Products

The definition and function of inventory management reveal the importance of modern industry in formulating policies that regulate the supply of raw materials, semi-finished products, and finished products. Unfortunately, most companies fail to consider the characteristics of their raw materials when determining inventory strategies. Raw materials that are perishable are those that consider their service life and storage time. Inventory management plays a crucial role in supply chain management, especially for perishable raw materials, such as food products. PT X, a food business in Padang, experienced difficulty in meeting the demand for rendang products due to a lack of raw materials. Therefore, this study aims to develop an inventory management model that takes into account the perishable raw materials' expiration time. The model development consists of three stages: model development design, inventory model formulation, and model testing. The proposed model resulted in a storage time interval of five days and an optimal order quantity of 34 kg of meat with a safety stock of 14 kg. Implementing this model led to lower total inventory costs for PT X than the actual conditions of the company. The total inventory cost obtained using this model is Rp279,797,822. This study emphasizes the importance of considering the characteristics of raw materials in determining inventory strategies to optimize inventory management effectively and efficiently. The study's findings can serve as a reference for other food businesses encountering similar inventory management challenges in the perishable food industry

Simulating the Impact of the Global Economic Crisis and Policy. Responses on Children in West and Central Africa

The current global financial and economic crisis, which exacerbates the impacts of the energy and food crises that immediately preceded it, has spread to the developing countries endangering recent gains in terms of economic growth and poverty reduction. The effects of the crisis are likely to vary substantially between countries and between individuals within the same country. Children are among the most vulnerable population, particularly in a period of crisis. Especially in least developed countries, where social safety nets programs are missing or poorly performing and public fiscal space is extremely limited, households with few economic opportunities are at a higher risk of falling into (monetary) poverty, suffering from hunger, removing children from school and into work, and losing access to health services. This study simulates the impacts of the global economic crisis and alternative policy responses on different dimensions of child welfare in Western and Central Africa (WCA) over the period 2009-2011. It is based on country studies for Burkina Faso, Cameroon, and Ghana, which broadly represent the diversity of economic conditions in WCA countries. In order to capture the complex macro-economic effects of the crisis and the various policy responses – on trade, investment, remittances, aid flows, goods and factor markets – and to then trace their consequences in terms of child welfare – monetary poverty, hunger (caloric poverty), school participation, child labour, and access to health services – a combination of macro- and micro-analysis was adopted. The simulations suggest that the strongest effects are registered in terms of monetary poverty and hunger, although large differences between countries emerge. More moderate impacts are predicted in terms of school participation, child labour, and access to health care, although these are still significant and require urgent policy responses. Specifically, Ghana is the country where children are predicted to suffer the most in terms of monetary poverty and hunger, while Burkina Faso is where the largest deteriorations in schooling, child labour and access to health services are simulated. Among the policy responses examined to counteract the negative effects of the crisis on child well-being, a targeted cash transfer to predicted poor children is by far the most effective program. A comparison between a universal and targeted approach is also presented.Global economic crisis, child poverty, hunger, education, child labour, health, West and Central Africa, Burkina Faso, Cameroun, Ghana, social protection

Inventory management and optimization: The Cavallone S.R.L. Business Case

Inventory management applicato ad un reale business cas