This thesis explores Centralised Demand Information Sharing (CDIS) in supply chains. CDIS is an information sharing approach where supply chain members forecast based on the downstream member’s demand. The Bullwhip Effect is a demand variance amplification phenomenon: as the demand moves upstream in supply chains, its variability increases. Many papers in the literature show that, if supply chain members forecast using the less variable downstream member’s demand, this amplification can be reduced leading to a reduction in inventory cost. These papers, using strict model assumptions, discuss three demand information sharing approaches: No Information Sharing (NIS), Downstream Demand Inference (DDI) and Demand Information Sharing (DIS). The mathematical analysis in this stream of research is restricted to the Minimum Mean Squared Error (MMSE) forecasting method. A major motivation for this PhD research is to improve the above approaches, and assess those using less restrictive supply chain assumptions. In this research, apart from using the MMSE forecasting method, we also utilise two non-optimal forecasting methods, Simple Moving Averages (SMA) and Single Exponential Smoothing (SES). The reason for their inclusion is the empirical evidence of their high usage, familiarity and satisfaction in practice. We first fill some gaps in the literature by extending results on upstream demand translation for ARMA (p, q) processes to SMA and SES. Then, by using less restrictive assumptions, we show that the DDI approach is not feasible, while the NIS and DIS approaches can be improved. The two new improved approaches are No Information Sharing – Estimation (NIS-Est) and Centralised Demand Information Sharing (CDIS). It is argued in this thesis that if the supply chain strategy is not to share demand information, NIS-Est results in less inventory cost than NIS for an Order Up To policy. On the other hand, if the strategy is to share demand information, the CDIS approach may be used, resulting in lower inventory cost than DIS. These new approaches are then compared to the traditional approaches on theoretically generated data. NIS-Est improves on NIS, while CDIS improves on the DIS approach in terms of the bullwhip ratio, forecast error (as measured by Mean Squared Error), inventory holding and inventory cost. The results of simulation show that the performance of CDIS is the best among all four approaches in terms of these performance metrics. Finally, the empirical validity of the new approaches is assessed on weekly sales data of a European superstore. Empirical findings and theoretical results are consistent regarding the performance of CDIS. Thus, this research concludes that the inventory cost of an upstream member is reduced when their forecasts are based on a Centralised Demand Information Sharing (CDIS) approach.

The thesis is focused on assessment of lean manufacturing methods, which are used in real company. The lean methods assessment is based on inventory management analysis in manufacturing company, which has these methods implemented. The thesis is divided into two main parts. Theoretical part maps the history of lean manufacturing, describes methods from which the concept consists of and compares approaches to lean methods analysis. Practical part of the thesis describes analysed company and lean methods, which are in the company implemented. In following part is presented analysis and the results, together with improvement proposal and own opinion regarding findings. The end of thesis summarizes results.

The thesis focuses on the analysis of various extensions of the classical multi-period single-item stochastic inventory problem. Specifically, we investigate two particular approaches of modeling risk in the context of inventory management: risk-averse models and robust formulations. We analyze the classical newsvendor problem utilizing a coherent risk measure as the objective function. Properties of coherent risk measures allow us to offer a unifying treatment of risk averse and min-max type formulations. We show that the structure of the optimal policy of the risk-averse model is similar to that of the classical expected value problem for both single and multi-period cases. The result carries over even when there is a fixed ordering cost. We expand our analysis to robust formulations of multi-period inventory problems. We consider both independent and dependent uncertainty sets and prove the optimality of base-stock policies for the general problem formulation. We focus on budget of uncertainty approach and develop a heuristic that can also be employed for a class of parametric dependency structures. We compare our proposed heuristic against alternative solution techniques.

In this study, carbon dioxide emissions resulting from transportation are assessed, carbon emission reduction opportunities in the current service supply chain design of Cisco Systems, Inc. are explored. Among these opportunities, changing transport mode from a high-carbon transport mode to a low-carbon transport mode is found to be the most promising option and is scrutinized. The effect of transportation mode change on carbon emission and expected total cost are scrutinized by developing a mathematical model that minimizes expected total cost subject to aggregate fill rate constraint. Furthermore, a second model that minimizes the expected total cost under aggregate expected fill rate and carbon emission constraints is developed. In this model transportation mode choice decisions are integrated into inventory decisions. Since it is difficult to make transportation mode selection for each individual item, the items are clustered and transportation mode selection is made for each cluster. Therefore we propose two clustering methods that are k-means clustering and an adopted ABC analysis. In addition, a greedy algorithm based on second model is developed. Since currently there are no regulations on carbon emissions, in order to examine possible regulation scenarios computational studies are carried out. In these studies, efficient solutions are generated and the most preferred solutions that have less carbon emission and lower total cost among all efficient solutions are examined.

Many supply chain problems involve discrete decisions in a dynamic environment. The inventory routing problem is an example that combines the dynamic control of inventory at various facilities in a supply chain with the discrete routing decisions of a fleet of vehicles that moves product between the facilities. We study these problems modeled as mixed-integer programs and propose a time decomposition based on approximate inventory valuation. We generate the approximate value function with an algorithm that combines data fitting, discrete optimization and dynamic programming methodology. Our framework allows the user to specify a class of piecewise linear, concave functions from which the algorithm chooses the value function. The use of piecewise linear concave functions is motivated by intuition, theory and practice. Intuitively, concavity reflects the notion that inventory is marginally more valuable the closer one is to a stock-out. Theoretically, piecewise linear concave functions have certain structural properties that also hold for finite mixed-integer program value functions. (Whether the same properties hold in the infinite case is an open question, to our knowledge.) Practically, piecewise linear concave functions are easily embedded in the objective function of a maximization mixed-integer or linear program, with only a few additional auxiliary continuous variables. We evaluate the solutions generated by our value functions in a case study using maritime inventory routing instances inspired by the petrochemical industry. The thesis also includes two other contributions. First, we review various data fitting optimization models related to piecewise linear concave functions, and introduce new mixed-integer programming formulations for some cases. The formulations may be of independent interest, with applications in engineering, mixed-integer non-linear programming, and other areas. Second, we study a discounted, infinite-horizon version of the canonical single-item lot-sizing problem and characterize its value function, proving that it inherits all properties of interest from its finite counterpart. We then compare its optimal policies to our algorithm's solutions as a proof of concept.

Background - A company’s distribution system is a critical component and businesses need to consider the aspects of customer service and total cost when designing the distribution system. A distribution system can be defined as the process of making products or services available for customers. The rise of e-commerce has increased the challenge of having a cost efficient distribution system together with a high standard of customer service.  The distribution system is put under heavy pressure to deliver goods as quickly as possible and at the lowest possible cost due to globalization and outsourcing. E-commerce involves a new approach of the distribution system with its small order sizes, daily order volumes and small parcel shipments that are often shipped the same day. Inventory management is being regarded as an important part of the distribution system. Inventory management is the ability to balance the demand of products with the supply of products in a cost-effectively way. Companies therefore need to use material planning methods to coordinate the flow of material effectively throughout the distribution system. Purpose - The purpose of this paper is to study Mionix’s current distribution system with focus on customer service and total cost. Based on the findings, this thesis will identify which costs that are possible to influence and reduce.  Secondly, the aim is to study how material planning methods can help Mionix to improve the inventory management function and propose measures for improvement. Method - This thesis has used a positivistic view with a deductive approach. It is a case study that contains elements of both qualitative and quantitative research strategy. In order to fulfil the purpose of the study the authors have conducted a flow and situational analysis in order to identify services and costs in the distribution system that Mionix can influence. Further, the authors conducted a situation analysis of Mionix’s current inventory management function. The authors then calculated and analysed how material planning methods such as EOQ, Total cost, Sensitivity analysis, Ordering points and optimal safety stock and service levels could improve Mionix’s inventory management function. Next, alternative solutions are presented together with the authors’ evaluations and recommendations for the company. The data that was needed to accomplish this was collected by performing interviews, observations and extracting data from computer system e.g. Excel. Conclusion - The authors have identified two distribution channels within the distribution system: the wholesaler channel and the retailers/e-commerce channel. Mionix has the opportunity to influence two particular costs: capital costs and cost of loss of sales, which are included in inventory- and customer service costs according to the total cost model. Material planning methods can improve Mionix’s inventory management function by deciding safety stock levels, ordering points and EOQ for all products in accordance with the theoretical framework. Further, if Mionix use the authors’ recommendation the company can reduce estimated total annual cost by 23% or 26% depending on what mode of transportation that is used

The development and application of inventory models for deteriorating items is one of the main concerns of the experts in the domain, since the number and variety of deteriorating products are dramatically increasing. One of the major gaps in the deteriorating inventories literature is that researchers have not paid enough attention to two important features in their models: i) Considering stochastic conditions; especially stochastic lead time is almost overlooked since makes the mathematical challenges complicated, ii) designing innovative inventory policies by taking into account the environmental issues and particularly the CO2 emission as a new objective in a multi-objective framework that is quite new. In this thesis, we study replenishment policy for deteriorating products under stochastic conditions in form of three different problem areas. In the first one, we develop a continuous (r,Q) inventory model for a retailer that offers a deteriorating product by considering infinite planning horizon, stochastic lead time, constant demand rate and backordered shortages. For modeling the deterioration process, a non-linear holding cost is defined. Taking into consideration the stochastic lead time as well as a non-linear holding cost makes the mathematical model more complex. We therefore customize the proposed model for a uniform distribution function that could be tractable to solve optimally by an exact approach. In second problem, we study the strategy of pooling lead time risks by splitting replenishment orders among multiple suppliers simultaneously for a retailer that sells a deteriorating product. Finally, in the last problem, we consider inventory and transportation costs, as well as the environmental impacts in a centralized supply chain by taking into account uncertain demand and partial backordered shortages. In order to deal with demand uncertainty, a two stage stochastic programming approach is taken. Then, by considering transportation vehicles capacity, we develop a mixed integer mathematical model. In this way, the best transportation vehicles and replenishment policy are determined by finding a balance between financial and environmental criteria. A numerical example from the real world is also presented to show the applicability and effectiveness of the proposed model.

Det är allt vanligare inom tredjepartslogistik att kunder hyr en yta för lagring. För den uthyrande parten, i detta fall Delta Terminal, är arean den begränsande faktorn för hur stor yta som kan hyras ut. Idag använ-der sig Delta Terminal av beslutsunderlag i form av lokalernas area och erfarenhet vart gods ska placeras och har inget hjälpmedel för att beräkna vart och hur mycket gods som kan allokeras för att använda så liten yta som möjligt. Studiens syfte har därför varit att ta fram ett faktabaserat hjälpmedel som kan användas som beslutsunderlag. För att uppnå syftet har en matematisk modell utvecklats för att optimera hur gods kan placeras till olika lokaler för att använda så liten area som möjligt och även kunna simulera förändringar. Modellen testades genom att jämföra den maximala godsvolym som lagrades 2012 mot optimeringsmodellens lösning baserat på samma gods- och lokaldata. De vanligaste godstyperna hos Delta terminal var bulk, storsäck och pall och användes i modellen. För dessa så approximerades den förväntade area- och volymåtgång vilket också gav beslutsfattaren en förväntad volymkapacitet för respektive lokal och gods. Resultatet i den optime-rade lösningen visade att ett av godsen skulle kunna flyttas till en annan lokal vilket skulle innebära att ungefär 25 procent mindre area används jämfört med den area som godsets placering upptar idag. Dessutom innebar den optimerade lösningen att tre lokaler frigjordes. Resultatet från simulering av volymkapaciteten för respektive gods och lokal kan hjälpa till vid en beslutssituation om en viss godsvolym får plats i lokalen eller inte och kan därmed hjälpa till att anpassa lokalens kapaci-tet mot godsets volym. Modellen fungerar teoretiskt och skulle kunna implementeras som ett användbart verktyg för beslutsfattaren i frågor som rör optimering eller simulering av ytorna. Vid en implementering gäller det emellertid att modellen valideras och jämförs mot verkliga utfall. / An increasingly common part in third party logistics is that customers rent an area for storage. For the party that leases out the area, in this case Delta Terminal, the area is the limiting factor for the amount of how much can be let out to lease. Today Delta Terminal uses decision sup-port in the form of premises area and experience where goods should be placed and have no means to calculate where and how much goods that can be allocated to use as small space as possible. The purpose of this study was therefore to develop a data based tool that can be used as support in the decision process. To achieve the objective a mathematical model was developed to optimize how freight can be placed at different locations to use as small an area as possible and also be able to simulate changes. The model was tested by comparing the maximum amount of cargo during 2012 against optimization model solution based on the same freight and local data. The most common goods handled at Delta Terminal were bulk, big bags and EUR-pallets and were used in the optimization model. For those goods an approximation of the expected area and volume was made that gave the decision maker an expected volume capacity for each local and goods. The result showed with the optimized solution that one of the goods could be moved to another storage place which would release approximate 25 percent reduction in area compared to where the goods are placed today and also three of the local spaces were released. The result from simulation of the volume capacity of each goods and local can help in a decision situation if a given volume of goods will fit in the local space and thus help to adapt the local capacity against the goods volume. Theoretically the model works and could be implemented as a useful tool for decision-makers on issues related to optimization or simulation of surfaces. However, when implementing the optimization model it is important to validate and compare the model’s result against actual outcomes.

The main goal of research is analysis of the inventory accounting methodics, to research the problems of inventory accounting in theory and practice and to make suggestions for improvement of inventory accounting by managing them. The aims of this research are: 1. To analyze the scientific and economical sources or literature and different legal bases, international and national standards concerning inventory accounting and its management. 2. To research the problems and their solutions linked with inventory accounting and its management. 3. To make suggestions for improving the methodics of inventory accounting and its management. The research methodics incorporates such methods: monographic, observation, logical analysis and synthesis, comparable analysis and diagrammatical. While exploring scientific and economical literature, national and international standards of accounting the problems concerning inventory accounting ant its management were obtained and solved.

Made available in DSpace on 2014-06-11T19:26:16Z (GMT). No. of bitstreams: 0 Previous issue date: 2008-12-05Bitstream added on 2014-06-13T20:34:06Z : No. of bitstreams: 1 rodrigues_pcc_me_bauru.pdf: 661198 bytes, checksum: fd2070d60a4818ea36d1e95ea50627af (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / As organizações industriais vêm adotando modelos produtivos que priorizam a redução de custos e aumento da qualidade de seus processos e produtos. Neste contexto a otimização e racionalização da gestão de estoques é uma grande oportunidade para estas empresas conquistarem estes objetivos. Para a realização desta pesquisa optou-se pela metodologia de estudo de casos múltiplos (dois casos), para atender o objetivo de analisar a gestão de estoques em duas empresas do setor gráfico localizadas na região de Bauru, na qual uma adota o sistema produtivo Engineering-To-Order (ETO) e a outra o sistema produtivo Make-To-Stock (MTS). O qual foi alcançado por meio da triangulação dos meios de coleta de dados, ou seja, entrevista semi-estruturada, análise documental e observação in-loco e estes tiveram como embasamento o referencial teórico. Por meio da triangulação das informações obtidas durante a coleta de dados, pôde-se elaborar a descrição da gestão de estoques e do sistema produtivo adotado em cada uma das empresas apresentadas nos estudos de caso e a análise cruzada. Após estes procedimentos foi elaborada a análise da influência do sistema produtivo sobre a gestão de estoques, no qual foram analisados os seguintes itens: produção, previsão de demanda, sazonalidade, layout, gestão de estoques, setup, logística de suprimentos e logística de distribuição. / Industrial organizations are adopting productive models that prioritize the reduction of costs and increase the quality of their processes and products. In this context the optimization and streamlining the inventory management is a great opportunity for these companies conquer these goals. To achieve this research methodology was chosen for the study of multiple cases (two cases), to meet to evaluate the inventory management in two companies in the sector chart located in the region of Bauru, in which one adopts the production system. Which was achieved by means of triangulation of data collection, i.e., semi-structured interviews, document analysis and observation in loco and they were light as the theoretical framework. Through triangulation of information obtained during data collection, it was possible to develop a descritption of the inventory management and the production system used in each of the companies presented in case studies and crossexamination. After these procedures were developed to analyze the influence of the production system on the inventory management, which were analyzed in the following: production, estimates of demand, seasonality, layout, inventory management, setup, logistics supplies and logistics of distribution. While reviewing the analysis of the influence of the production system on the management of inventories could be observed some differences in relation to the literature, they are: logistics supply, distribution, inventory management, production systems Make-To-Stock and Engineering-To-Order.