This paper is an exploratory case study of a logistics cost problem at Dep. X, and the normative purpose is to develop a model for Dep. X to aid in solving the problem of large damage costs. Dep. X is the logistic department of a warehouse located in a midsized Swedish city. The warehouse is part of an international furniture chain that operates in more than 40 countries worldwide and has an annual turnover of 211 billion Swedish SEK. This company has a clear cost focus and therefore, it is very important for the different departments to keep costs at a minimum. The problem that Dep. X is facing is related to damaged products, which can be further divided into Delivery Damages [DDs] (damages that are inflicted on products before the freight reaches the department) and Warehouse Damages [WDs] (damages that occur at the department). The warehouse has tried to solve the problem by forming a unit called ‘Cost hunters’. This group has some suspicions but has not yet found out the underlying reasons for the damaged goods. The thing that they know is that this is an unproportionally large cost for the warehouse, compared to other warehouses. In order for the researchers to investigate the cost issue, an abductive research strategy was used. The authors found out in an early stage of the research process that the problem was related to WDs and after a pre-study hypothesized four different problem areas to investigate: <ul type="disc">Flaws in Communicating Knowledge Flaws in Working Environment Flaws in Motivation Flaws Concerning Customers In order to establish whether or not these hypotheses were correct, a benchmarking study was conducted with a department under the same company, which was of basically the same size. Apart from the pre-study, a total of nine interviews were conducted; five at Dep. X and four at Dep. Y. The researchers also sent out surveys to both departments, conducted a damage levels study and had a meeting with a group manager at the distribution central in order to collect the needed information. After data collection, the data were processed and analyzed, and the researchers came to the conclusion that the problem with high WDs at Dep. X was related to, firstly, flaws in communicating knowledge and flaws in the working environment. The two other problem areas, flaws in motivation and flaws concerning customers, were also to some extent related to WDs, but this impact was not considered enough to be a major cause. The authors finish the thesis by illustrating with a model how the problems seem to have arisen and by suggesting improvement areas to deal with in order to eliminate the cost issue.

Supply chain management complexity is a growing challenge for a broad range of contemporary companies, which makes them turn to new and increasingly advanced IT-systems as a salvation. One of the currently most important system in a supply chain manager’s toolbox is the warehouse management system. As business challenges increases so does also the complexity in the investment processes surrounding the warehouse management systems, this paper explores value creation in these processes to understand the resource exchanges involved, the exchange actor’s different roles and the implications of interactions between the actors. This is conducted through a case study with a market leading warehouse management system vendor and a supply chain intensive customer. The findings indicate that value creation in a complex warehouse management system investment entails several intervened and ongoing processes of different resource exchanges, were the actors co-create value jointly by sharing, combining and utilizing the resources throughout these processes. In order to establish this essential value co-creation sphere, also social exchanges in the form of qualitative interactions between the actors have proven to be a fundamental factor.

The objective of this project is to improve productivity and efficiency for the inbound material handling operations in the warehouse of DC Älmhult. After three weeks pre-study in place of the distribution center, the authors have observed several problems existing in the current production, among which three types of wastes are found and analyzed by using VSM that are pick and drop, operator waiting time and inefficient transport. Two typical cases chosen from the inbound production are analyzed to reflect the current process and address problems. Fish-bone tool is used to identify wastes and roots. To eliminate or reduce the wastes, recommendations and solutions are developed by creating continuous flow combining with internal transport optimization. Future-state VSMs are drawn based on the suggested changes in line with continuous flow. Different productions models are simulated by elaborately developed excel sheets. A „distance table‟ is developed by using Microsoft Excel to help the loading or unloading leaders with the gate steering function so as to minimize internal transport distance. A new layout of the conveyor system is also suggested to lower the idle transport rate.

Nowadays in the world of mass consumption there is big demand for distributioncenters of bigger size. Managing such a center is a very complex and difficult taskregarding to the different processes and factors in a usual warehouse when we want tominimize the labor costs. Most of the workers’ working time is spent with travelingbetween source and destination points which cause deadheading. Even if a worker knowsthe structure of a warehouse well and because of that he or she can find the shortest pathbetween two points, it is still not guaranteed that there won’t be long traveling timebetween the locations of two consecutive tasks. We need optimal assignments betweentasks and workers.In the scientific literature Generalized Assignment Problem (GAP) is a wellknownproblem which deals with the assignment of m workers to n tasks consideringseveral constraints. The primary purpose of my thesis project was to choose a heuristics(genetic algorithm, tabu search or ant colony optimization) to be implemented into SAPExtended Warehouse Management (SAP EWM) by with task assignment will be moreeffective between tasks and resources.After system analysis I had to realize that due different constraints and businessdemands only 1:1 assingments are allowed in SAP EWM. Because of that I had to use adifferent and simpler approach – instead of the introduced heuristics – which could gainbetter assignments during the test phase in several cases. In the thesis I described indetails what ware the most important questions and problems which emerged during theplanning of my optimized assignment method.

Inom utvecklingen av de flesta typer av datorsystem används datormodeller för att strukturera lagringen och användningen av data. Likaså finns det flera olika datamodelleringsmetoder att välja bland för detta ändamål. I samarbete med ett företag har en fallstudie genomförts med syfte att undersöka hur agiliteten i två av dessa metoder påverkar utvecklingen av ett Data Warehouse (DW).  De två datamodelleringsmetoder som undersökts är Data Vaulting och Hyper Agility och arbetet har fokuserat på att undersöka skillnaderna mellan dessa när det gäller mängden ETL-kod som måste skrivas, funktionaliteten i datatransformationerna, möjligheten till att uppdatera systemstrukturen samt den totala kostnaden för utvecklingen av DW-lösningen. Inom ramen för fallstudien har en litteraturstudie genomförts och kombinerats med material från sex intervjuer, där respondenterna varit konsulter såväl som företagsrepresentanter.   Resultaten av fallstudien visar att respektive metods agilitet har en stor påverkan på den kod som utvecklas. Ju högre agilitet metoden har desto mindre kod, tid och andra resurser som krävs. Dock medför även en förhöjd agilitet större komplexitet samt eventuell risk för ett misslyckat utvecklingsprojekt.

Along with the rapid expansion of information technology and the urgent demand of Decision Support System, only in a few years, data warehouse have been converting absolute theory into practical technology. More and more enterprises have been plunging into the data warehouse system for supporting business process and decision. Data warehouse system does transfer big data of enterprise to useful resource or information and will not impact current history data. The data warehouse depends on enterprise various demands and plays the role of Decision Support System. It is the reason that enterprise pays attention and positive investment. This paper identifies as a set of evaluating criteria on the literature review and consults the expert to decide vendor level, design the questionnaire and retrieve weight. At last the paper uses the real case evaluating data warehouse system by ELECTRE I. The result of this study can not only contribute to the understanding of functionalities of a data warehouse system but can provide a practical guideline for selection of a data warehouse system.

Data warehouses contain data consolidated from several operational databases and provide the historical, and summarized data which is more appropriate for analysis than detail, individual records. On-Line Analytical Processing (OLAP) provides advanced analysis tools to extract information from data stored in a data warehouse. Fast response time is essential for on-line decision support. A bitmap index could reach this goal in read-mostly environments. When data has high cardinality, we prefer to use the Range-Based Index (RBI), which divides the attributes values into several partitions and a bitmap vector is used to represent a range. With RBI, however, the number of records assigned to different ranges can be highly unbalanced, resulting in different search times of disk accesses for different queries. Wu et al proposed an algorithm for RBI, DBEC, which takes the data distribution into consideration. But the DBEC strategy could not guarantee to get the partition result with the given number of bitmap vectors, PN. Moreover, for different data records with the same value, they may be partitioned into different bitmap vectors which takes long disk I/O time. Therefore, we propose the IPDF, CP, CP* strategies for constructing the dynamic range-based indexes concerning with the case that data has high cardinality and is not uniformly distributed. The IPDF strategy decides each partition according to the Probability Density Function (p.d.f.). The CP strategy sorts the data and partitions them into PN groups for every w continuous records. The CP* strategy is an improved version of the CP strategy by adjusting the cutting points such that data records with the same value will be assigned into the same partition. On the other hand, we could take the history of users' queries into consideration. Based on the greedy approach, we propose the GreedyExt and GreedyRange strategies. The GreedyExt strategy is used for answering exact queries and the GreedyRange strategy is used for answering range queries. The two strategies decide the set of queries to construct the bitmap vectors such that the average response time of answering queries could be reduced. Moreover, a bitmap index consists of a set of bitmap vectors and the size of the bitmap index could be much larger than the capacity of the disk. We propose the FZ strategy to compress each bitmap vector to reduce the size of the storage space and provide efficient bitwise operations without decompressing these bitmap vectors. Finally, from our performance analysis, the performance of the CP* strategy could be better than the CP strategy in terms of the number of disk accesses. From our simulation, we show that the ranges divided by the IPDF and CP* strategies are more uniform than those divided by the DBEC strategy. The GreedyExt and GreedyRange strategies could provide fast response time in most of situations. Moreover, the FZ strategy could reduce the storage space more than the WAH strategy.

Data warehouses contain data consolidated from several operational databases and provide the historical, and summarized data which is more appropriate for analysis than detail, individual records. On-Line Analytical Processing (OLAP) provides advanced analysis tools to extract information from data stored in a Data Warehouse. OLAP is designed to provide aggregate information that can be used to analyze the contents of databases and data warehouses. A range query applies an aggregation operation over all selected cells of an OLAP data cube where the selection is specified by providing ranges of values for numeric dimensions. Range sum queries are very useful in finding trends and in discovering relationships between attributes in the database. There is a method, prefix sum method, promises that any range sum query on a data cube can be answered in constant time by precomputing some auxiliary information. However, it is hampered by its update cost. For today's applications, interactive data analysis applications which provide current or "near current" information will require fast response time and have reasonable update time. Since the size of a data cube is exponential in the number of its dimensions, rebuilding the entire data cube can be very costly and is not realistic. To cope with this dynamic data cube problem, several strategies have been proposed. They all use specific data structures, which require extra storage cost, to response range sum query fast. For example, the double relative prefix sum method makes use of three components: a block prefix array, a relative overlay array and a relative prefix array to store auxiliary information. Although the double relative prefix sum method improves the update cost, it increases the query time. In the thesis, we present a method, called the recursive relative prefix sum method, which tries to provide a compromise between query and update cost. In the recursive relative prefix sum method with k levels, we use a relative prefix array and k relative overlay arrays. From our performance study, we show that the update cost of our method is always less than that of the prefix sum method. In most of cases, the update cost of our method is less than that of the relative prefix sum method. Moreover, in most of cases, the query cost of our method is less than that of the double relative prefix sum method. Compared with the dynamic data cube method, our method has lower storage cost and shorter query time. Consequently, our recursive relative prefix sum method has a reasonable response time for ad hoc range queries on the data cube, while at the same time, greatly reduces the update cost. In some applications, however, updating in some regions may happen more frequently than others. We also provide a solution, called the weighted relative prefix sum} method, for this situation. Therefore, this method can also provide a compromise between the range sum query cost and the update cost, when the update probabilities of different regions are considered.

Taiwan is the major country of importing LNG. In this paper discussed LNG cold energy recovery used in cold storage warehouse and other energy conservation systems. In the cold storage warehouse systems that showed the less temperature of cold storage warehouse the more exergy efficiency and the best exergy efficiency is 30%. Base on thermoeconomic analysis there was the optimal operation temperature at -70¢J. In the purifier nitrogen system (PNS), the investigation indicated the best efficient operating temperature at -150¢J. But with economic analysis the optimal design temperature of this PNS was -130¢J. And the last energy conservation system was the running power plane. In this research studied the power planes used LNG cold energy as inlet air-cooling systems. According to the investigation that showed the systems increased power output up to 14.4¢H in the 4.5¢J of inlet air cooling temperature. And these systems also improved the heat rate of power planes about 0.98%. The conclusions presented that the potentialities of LNG cold energy are huge, and with proper engineering and economic analysis could make these energy conservation systems more feasible.

Rising competition among retailers, coupled with the economic recession and its influence on the consumers' cautiousness in consumption causes private label to become a new profit protection policy for the retailer industry. Private label symbolizes that retailers control the channel. As consumers recognize private label more , it will gradually influence the public¡¦s consumption attitude. The research conducted among three successful private label retailers and used the case interview. Aimed at the product features, brand equity, pricing strategy, promotion and channel of private label products and used different dimensions to probe into each case company¡¦s strategy. The private label strategy of retailers is summarized through the categorization analysis . The survey of the consumer behavior are framed six items: product features, brand equity, price, promotion, channel and service , then do the questionnaire survey on Costco consumers who purchase private label. Also view the satisfaction condition from Costco consumer with regards to private label. The results and conclusions are as follows: retailers mainly focus on private label products that provide quicker circulation and economies of scale. As long as the retailer can provide products whose quality is similar to national brand products at a more competitive price, consumers may choose private label products of good quality and price. Furthermore, in the aspect of promotion, retailers commonly adopt the DM , choosing several private label products to sell at a lower price than promotion price. Finally, in the aspect of channel, due to the less popularity of private label products than national brand product, the retailers have to attract consumers through the national brand in order to give a chance to private label through channel advantage. For example, intensive advertisement inside stores can influence the consumer¡¦s choice by placing private label in the area of consumer¡¦s eye sight zone. Lastly, this study and consumer survey proposes recommendations for retailers based on understanding customer need.