Graduate

'Lean Manufacturing' is a production practice that aims to reduce shop floor inventory in a manufacturing firm. Its origins extending deep into Japanese history, manufacturing works on tight material control policies and aims to achieve as close to 'stockless production' and 'zero inventories' as possible. The goals of Lean Manufacturing or the seven zeroes (zero defects, setup time, breakdowns, handling, lead time and surging) hence all strive to achieve zero inventory by producing what is needed when needed, thereby eliminating storage costs and capital tied up in inventory. The history of manufacturing in America is explored and compared to that of far eastern societies. This thesis then introduces the development of JIT, Lean Manufacturing and their immediate vii effects on the world. Techniques are explored for implementing lean methods in an automobile manufacturing firm – whether (and how) an automobile manufacturer can bring down his costs using the same and what changes will need to be done to their existing manufacturing processes. Advantages, disadvantages and possible setbacks one may encounter while attempting to implement lean methods are also explored. / text

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Small wetlands are often ignored in inventory studies; consequently they are less protected and therefore more vulnerable. Moreover, previous research indicates the importance of small wetlands as they can provide important ecosystem services to human kind. The Environmental Protection Agency of Sweden has carried out a national wetland inventory, however they have applied a limited area, which consequently excludes smaller wetlands. This study aims to make an inventory of the excluded wetlands smaller than 10 hectares in Laholms municipality, Halland. In this inventory study I have applied GIS as a method by comparing different map layers, such as aerial photos, land cover data and Google Earth. Furthermore, the study aims to investigate the ecosystem services provided by the located wetlands in the study area and discuss how this exclusion could affect the services. The results of the inventory indicate that 745 wetlands are missing in the Environmental Protection Agency inventory, which correspond to 12 percent of the total wetlands in Laholms municipality. The results also indicate that 99,1 percent of the missing wetlands are mire and 0,9 percent are riparian wetlands. In the literature study I found that mire provides ecosystem services such as carbon storage, material such as peat, and unique habitats for biodiversity. Riparian wetlands provide ecosystem services such as unique habitats for biodiversity, improving the quality of the water, reduce fertilization and provide recreational values. Moreover, both type of wetlands are also important to the wetland mosaic in order to maintain proliferation and the local hydrological systems.  Additionally, small wetlands are especially important to invertebrates and amphibians. Though, if the small wetlands in Laholms municipality continue to be ignored then the benefits of the ecosystem services mentioned above are likely to be reduced and limited.

In this thesis, we study the statistical issues in lost sales inventory systems, focusing on the complexity arising from the stochastic demand. We model the demand by the Zero Inflated Poisson (ZIP) distribution. The maximum likelihood estimator of the ZIP parameters taking censoring into account are derived separately for the newsvendor and the (s, S) inventory systems. We also investigate the effect of the estimation errors on the optimal policies and their costs. We observe from a simulation study that the MLE taking censoring into account performed the best in terms of cost as well as policy among various estimates. We then proceed to develop a Bayesian dynamic updating scheme of the ZIP parameters. It is applied to the newsvendor system. We perform a simulation study to investigate the advantage of the Bayesian updating approach over the traditional MLE approach. We conclude that the Bayesian pproach offers a better learning technique when one lacks of good understanding of the demand pattern in the first few periods. Since inventory policy affects the information acquisition and-the demand distribution updating process, how to determine the optimal inventory policy when the demand distribution is yet to be learned is the focus of the latter part of the thesis. We investigate the effect of demand censoring on the optimal policy in newsvendor inventory models with general parametric demand distribution and unknown parameter values. We provide theoretical proof of the conjecture that it is better off to adopt a higher than the myopic optimal policy in the initial periods when demand is learned in a censoring system. We show that the newsvendor problem with observable lost sales reduces to a sequence of single-period problems while the newsvendor problem with unobservable lost sales requires a dynamic analysis. We explore the economic rationality for this observation and illustrate it with numerical examples.

Chain of custody in the forest sector is very dependent on effectively tracking products though the supply chain and manufacturing processes, including sawmilling, drying, planing, and pulp processes. The effectiveness of a tracking system is largely influenced by the characteristics of the process it works within, the nature of the tracking system being used, and increasingly by the penetration of technologically advanced material tracking methods into on-the-ground CoC practices. A variety of CoC systems that exist in the global marketplace accommodate the use of advanced materials tracking systems as a tool for their their implementation. These advances not only offer the potential to reinforce the traceability of products in inventory, but also promote maintenance of their certified status between the various organizations that exist along the wood product supply chain, and ultimately to the end consumer. In the past, a number of different product tracking methods have been used, all of which suffer certain shortcomings in the challenging environment of the forest industry, and the extremely complex nature of Chain of Custody tracking. This work explores the development of a novel material tracking method using the innate IR signatures of polymeric compounds, varied by compound and concentration to develop millions of potential combinations, and consequently millions of unique identities. The combined variation of multiple IR peak frequencies and magnitudes provide the conceptual basis of a chemical barcode system, named "Chemi-Code", to be explored. To prove the validity of this concept, a series of polymers were assayed for suitability in such a system by tracking their IR response stability in the presence of solar UV radiation and over time. As well, the feasibility of varying polymer concentration, and subsequently identification of concentrations by DRIFT spectroscopy was explored by constructing response curves between polymer concentration and peak absorbance, and assessing associated error. Seven polymers were identified and assessed. Only two of these polymers were found to be sufficiently stable for use in the context of the forest industry, and of those two, only one behaved in a manner that would allow peak absorbance to be used as an identifiable chemical variable. Although only one of the seven polymers was suitable for use in the "Chemi-Code" system, the study did demonstrate the validity of the concept by showing that polymers can be exploited for use in such a system.

This simulation study considers a low-volume manufacturing system, which produces complex, customized electronics. Modeling demand as a renewal-reward process, the simulation, inspired by the production system and available data from a Canadian company, examine the performance of alternative inventory policies and operating procedures. Performance indicators that measure the responsiveness and inventory on hand show trade-offs between them in order to supply relevant information to decision makers. Experiments compare make-to-order and make-to-stock scenarios with various inventory parameters as well as introducing variability to examine the model’s robustness under uncertainty. The system under consideration consists of three main processes to manufacture a finished product from raw materials. The first process fabricates metal and electrical components from raw materials. Second, a worker assembles components into a semi-finished product. The third requires information from the customer in order to customize the product according to their needs, and test the unit to ensure its quality. The company, known for their well-designed products and exceptional customer service, wants to improve the accuracy of their leadtime promising. The current MRP control system assumes a completely make-to-order environment where every piece of WIP has a customer order attached to it. However, a forecast of orders likely to materialize from the sales quotes allows production to initiate jobs before the actual order arrives. The approach taken to analyzing this system involves studying the make-to-stock, make-to-order decision at two stock points, components and semi-finished units. The operating procedures examine four possible stocking strategies: holding no inventory, holding only component or semi-finished inventory, and holding both components and semi-finished units. Simulation experiments determine the trade-off between holding inventory and the responsiveness to the customer for each operating procedure. Sources of randomness introduced to processing time, capacity, and demand, show how they respond to added variability. The simulation experiments indicate that holding no inventory, and waiting for a customer order to initiate jobs, results in unstable performance. In order to achieve a stable make-to-order system, it would be necessary to have a fifty percent reduction in demand or product cycle time, a capacity expansion, or forecasting method. In the absence of an accurate forecast model, holding inventory is necessary for an acceptable level of performance. Component inventory is useful as many components are common among a number of products. Suitable component inventory can lead to customer orders typically fulfilled within two weeks. Adding semi-finished inventory can reduce the customer lead-time to under a week though requires stocking at least a few of each semi-finished unit. Holding semi-finished inventory without component stock is possible. However, it is necessary that the replenishment quantity be three or more units ordered at a time. Otherwise, the setup time for components exceeds the allowable limits and resource queues become unstable, much like the completely make-to-order scenario. Using an order-up-to parameter for semi-finished stock can further decrease the setup time incurred per unit. The model is robust to randomness in job times, though it is component stock, which provides an effective buffer to this variability. Machine breakdowns begin to affect responsiveness measures if the average time for repair is greater than a week. Reducing the capacity in the assembly and testing processes can provide the same level of service indicating the two resources are underutilized. The analysis of this system shows the current make-to-order model requires some forecast to function in steady state, which is difficult to model without information on the current forecasting processes. Expanding the simulation model to incorporate forecasting or some other means of analysis can improve its accuracy and credibility as a management decision tool.

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