<p>Demand has become increasingly difficult to forecast in today’s volatile markets. Being able to produce towards real demand is becoming vital for companies, since inventories of finished goods are expensive to maintain and because miscalculated products tie up capital that in the end is never repaid. More and more companies are using postponement strategies to delay the process of producing until real demand has become known. </p><p>Tooling Support Halmstad is a company within the manufacturing industry, which has become aware of the benefits with postponement strategies for parts of their production. In the year of 2006 Tooling Support Halmstad implemented a neutral stock for taps, their largest product. The target was to reduce their lead time and capital tied up.</p><p>The purpose of this report is to evaluate Tooling Support Halmstad’s achievements, regarding improvements of lead time and capital tied up, in effect of the implementation of a neutral stock. The neutral stock’s impact on Tooling Support Halmstad’s production and inventory strategy will be described in order to fully understand the most important factors when implementing a neutral stock. This study will not examine all factors arising from implementation of a neutral stock, since that would make it unreasonable extensive. The time periods examined in this report is the last quarter of 2005 and the first quarter of 2007. This has been done in order to compare the situation before the neutral stock with the situation after the implementation. This case study has used qualitative research methods. A small number of persons, from different parts of the organisation, have been interviewed in order to deeply evaluate this specific situation.</p><p>The result shows that the implementation of a neutral stock has been beneficial for Tooling Support Halmstad. Their lead time has decreased drastically and their level of service towards the central warehouse has improved as well. It exist strong indications of a decrease in capital tied up, even though any specific values have not been possible to provide.</p>

This Record of Study contains the details of an optimization model developed for Shell Oil Co. This model will be used during the strategic design process of a supply chain for a new technology commercialization. Unlike traditional supply chain deterministic optimization, this model incorporates different levels of uncertainty at suppliers' nominal capacity. Because of the presence of uncertainty at the supply stage, the objective of this model is to define the best diversification and safety stock level allocated to each supplier, which minimize the total expected supply chain cost. We propose a Monte Carlo approach for scenario generation, a two-stage non-linear formulation and the Sample Average Approximation (SAA) procedure to solve the problem near optimality. We also propose a simple heuristic procedure to avoid the nonlinearity issue. The sampling and heuristic optimization procedures were implemented in a spreadsheet with a user's interface. The main result of this development is the analysis of the impact of diversification in strategic sourcing decisions, in the presence of stochastic supply disruptions.

This Record of Study contains the details of an optimization model developed for Shell Oil Co. This model will be used during the strategic design process of a supply chain for a new technology commercialization. Unlike traditional supply chain deterministic optimization, this model incorporates different levels of uncertainty at suppliers’ nominal capacity. Because of the presence of uncertainty at the supply stage, the objective of this model is to define the best diversification and safety stock level allocated to each supplier, which minimize the total expected supply chain cost. We propose a Monte Carlo approach for scenario generation, a two-stage non-linear formulation and the Sample Average Approximation (SAA) procedure to solve the problem near optimality. We also propose a simple heuristic procedure to avoid the nonlinearity issue. The sampling and heuristic optimization procedures were implemented in a spreadsheet with a user’s interface. The main result of this development is the analysis of the impact of diversification in strategic sourcing decisions, in the presence of stochastic supply disruptions.

THE ADVANTAGE OF RFID TECHNOLOGY IMPLEMENTATION IN A MANUFACTURING FIRM. THE TECHNOLOGY IMPLEMENTATION STREAM LINES THE LOSS OF INFORMATION FLOW WHEN THE PRODUCT MOVES ALONG THE DIFFERENT CHAIN MEMBERS. THE COMMON SHARING OF THE ASSOCIATED BENEFIT BRINGS HIGHER PROCESS EFFICEINCY , WHEN THE PRODUCT MOVES ALONG THE UPSTREAM AND DOWNSTREAM SUPPLY CHAIN FOR THE SELECTED PRODUCT. THE IMPLEMENTATION IS A CUSTOMISED SOLUTION FOR THE MANUFACTURING UNIT FOR ITS PRODUCT, THIS THESIS WILL ENABLE THE IMPLEMENTATORS THE VALUABLE IMPLEMENTATION PROCEDURES THAT ONE HAS TO FOLLOW TO TAKE RIGHT BENEFIT FROM THIS TECHNOLOGY.

Demand has become increasingly difficult to forecast in today’s volatile markets. Being able to produce towards real demand is becoming vital for companies, since inventories of finished goods are expensive to maintain and because miscalculated products tie up capital that in the end is never repaid. More and more companies are using postponement strategies to delay the process of producing until real demand has become known. Tooling Support Halmstad is a company within the manufacturing industry, which has become aware of the benefits with postponement strategies for parts of their production. In the year of 2006 Tooling Support Halmstad implemented a neutral stock for taps, their largest product. The target was to reduce their lead time and capital tied up. The purpose of this report is to evaluate Tooling Support Halmstad’s achievements, regarding improvements of lead time and capital tied up, in effect of the implementation of a neutral stock. The neutral stock’s impact on Tooling Support Halmstad’s production and inventory strategy will be described in order to fully understand the most important factors when implementing a neutral stock. This study will not examine all factors arising from implementation of a neutral stock, since that would make it unreasonable extensive. The time periods examined in this report is the last quarter of 2005 and the first quarter of 2007. This has been done in order to compare the situation before the neutral stock with the situation after the implementation. This case study has used qualitative research methods. A small number of persons, from different parts of the organisation, have been interviewed in order to deeply evaluate this specific situation. The result shows that the implementation of a neutral stock has been beneficial for Tooling Support Halmstad. Their lead time has decreased drastically and their level of service towards the central warehouse has improved as well. It exist strong indications of a decrease in capital tied up, even though any specific values have not been possible to provide.

No description available.

La industria es comúnmente vista como una fuente de degradación ambiental y de consumo de recursos, a pesar de ello es una parte vital del desarrollo social y de la creación de riqueza. Del mismo modo, los sistemas industriales causan y determinan los flujos de materias y energía a través de la sociedad. El desarrollo sostenible está asociado a todos los aspectos anteriores al englobarlos a todos.Los servicios sostenibles son aquellos que restringen el consumo de recursos y generación de residuos a un nivel aceptable considerando las existencias y las velocidades de recuperación de los recursos así como la capacidad de soporte de La Tierra. Asimismo, hacen una contribución positiva a la satisfacción de las necesidades humanas y proveen de valor económico a la empresa. La selección de procesos apropiados para la provisión de un dado servicio es el tópico principal de esta tesis.Esta tesis presenta un marco consistente para el soporte a la decisión hacia alternativas sostenibles. El marco abarca un grupo de métodos y herramientas aplicables al soporte de la decisión en cuestiones de diseño, actualización, y operación considerando criterios de sostenibilidad en términos económicos y medioambientales. Se ha enfatizado la simulación de procesos, el modelado matemático y otros métodos de estadística multivariable. El marco está materializado en un procedimiento de uso que posee cuatro pasos que imitan los de otros métodos actualmente utilizados y un set integrado de herramientas. Las herramientas usadas son en todos los casos modelos matemáticos que permiten una representación precisa de la realidad que simulan. El problema multiobjetivo resultante es resuelto usando una estrategia que permite restringir la mejor solución de compromiso. Una multitud de casos de estudio industriales muestra la forma de aplicación del marco en diferentes escenarios.El marco se ha aplicado a casos de estudios que requieren de soporte a la decisión. El caso de diseño de procesos continuos se ha incluido tratando tres casos. El primero está relacionado con la selección de opciones de tratamiento de aguas residuales en una planta de producción de ácido fosfórico considerando incertidumbre en variables operativas. Otro caso considera las decisiones relacionadas al uso de diferentes materias primas en una usina eléctrica con tecnología de gasificación. El último caso considera la optimización de las variables operativas en el diseño de un sistema de destilación reactiva. Todos los casos son modelados rigurosamente usando noveles herramientas de simulación y modelado en conjunto con otras desarrolladas para el análisis de los aspectos económicos y medioambientales de la sostenibilidad.Posteriormente, se ha estudiado el problema operacional de la selección de la planificación de producción. En este caso se ha puesto atención especial a la selección de métricas apropiadas considerando aspectos económicos, medioambientales y de eficiencia que reflejen las características secuenciales del problema. El modelo propuesto se ha construido usando herramientas de programación matemática y la producción de fibras acrílicas es la aplicación considerada.Finalmente el marco se ha aplicado al diseño y planificación de una cadena de producción. En este caso se modelan decisiones de planificación a medio y largo plazo y se las aplica a la producción de anhídrido maleico en Europa del Oeste. Dadas las características del problema se han estudiado diferentes instrumentos económicos asociados al medio ambiente, como la venta de permisos de emisión y subsidios a la producción. Esto permite mostrar las capacidades del marco para el estudio de políticas gubernamentales.Los casos de estudio muestran las diferentes compensaciones que aparecen en varios niveles de decisión. Asimismo el marco provee con un enfoque robusto para la trazabilidad y capacidad de verificación de las diferentes hipótesis de modelado, lo cual refuerza el proceso de toma de decisiones. / Industry is often seen as a source of environmental degradation and resource depletion, however it is a vital part of societal development and wealth creation. Moreover, industrial systems cause and determine flows of materials and energy through the society. Sustainable development is associated to all the former issues, by encompassing them altogether under the same umbrella.Sustainable services are those, that restrain resource consumption and waste generation to an acceptable level, considering Earth's existing capital, rates of replenishment and carrying capacity, make a positive contribution to the satisfaction of human needs, and provide enduring economic value to the business enterprise. The selection of appropriate processes for providing a given sustainable service is the main topic of this thesis. This thesis presents a consistent framework for decision support towards sustainable design. It encompasses a set of methods and tools applicable to decision aid in process design, retrofit and operation considering sustainability criteria in terms of economic and environmental issues. In this sense special consideration is given to process simulation, general modelling programs and other multivariate statistical methods, as well as their supporting associated tools. The framework is materialised as a procedure for its application in four steps, which mimics other current applied methods; and a set of tools which are integrated. One of the framework aims is the consideration of the uncertainty associated to parameters and values. The tools, which in all cases are mathematical models, allow for an accurate representation of the reality they simulate. In the case of alternatives generation problem, the resultant multiobjective optimisation problem is solved by an strategy that permits narrowing-in the best solution compromise. A multitude of industrial case studies teaches the way to use the framework in different scenarios.The framework is applied to different case studies which require decision aid. The case of continuous process design is first addressed along with three different studies. The first one is related to the selection of waste water treatment options for a phosphoric acid plant considering uncertainty in operating variables, another analysis considers the decisions related to raw material management in an integrated gasification combined cycle power plant, while the last one addresses the design of a reactive distillation system considering optimisation of operating variables. All case studies are modelled rigorously using state of the art commercial simulation tools in conjunction with other tools developed for the assessment of sustainability concerns, mainly economic and environmental issues. The operational problem of selecting appropriate schedules, for the production of different products, is addressed next. In this case, special attention is given to the selection of appropriate metrics, considering economic, efficiency and environmental concerns that reflect the sequence dependence features of this problem. The model proposed is built using mathematical programming and the production of acrylic fibres is the application considered. Finally, the framework is applied to the design and retrofit of the whole chemical supply chain. Mid- to long-term planning decisions are modelled in this case, which studies a maleic anhydride production supply chain in Western Europe. Due to the problem nature, economic-environmental instruments such as emission trading and price subsidies are studied showing the viability of the presented approach for policy analysis.The case studies and the proposed framework show that different trade offs appear at different decision making levels. Moreover, the framework provides with a robust approach for traceability and verifiability of different modelling hypothesis which strengthens the decision making process.

This Record of Study contains the details of an optimization model developed for Shell Oil Co. This model will be used during the strategic design process of a supply chain for a new technology commercialization. Unlike traditional supply chain deterministic optimization, this model incorporates different levels of uncertainty at suppliers’ nominal capacity. Because of the presence of uncertainty at the supply stage, the objective of this model is to define the best diversification and safety stock level allocated to each supplier, which minimize the total expected supply chain cost. We propose a Monte Carlo approach for scenario generation, a two-stage non-linear formulation and the Sample Average Approximation (SAA) procedure to solve the problem near optimality. We also propose a simple heuristic procedure to avoid the nonlinearity issue. The sampling and heuristic optimization procedures were implemented in a spreadsheet with a user’s interface. The main result of this development is the analysis of the impact of diversification in strategic sourcing decisions, in the presence of stochastic supply disruptions.

The Planning of Supply Chain Management System for Industrial Materials Intermediary

This Record of Study contains the details of an optimization model developed for Shell Oil Co. This model will be used during the strategic design process of a supply chain for a new technology commercialization. Unlike traditional supply chain deterministic optimization, this model incorporates different levels of uncertainty at suppliers' nominal capacity. Because of the presence of uncertainty at the supply stage, the objective of this model is to define the best diversification and safety stock level allocated to each supplier, which minimize the total expected supply chain cost. We propose a Monte Carlo approach for scenario generation, a two-stage non-linear formulation and the Sample Average Approximation (SAA) procedure to solve the problem near optimality. We also propose a simple heuristic procedure to avoid the nonlinearity issue. The sampling and heuristic optimization procedures were implemented in a spreadsheet with a user's interface. The main result of this development is the analysis of the impact of diversification in strategic sourcing decisions, in the presence of stochastic supply disruptions.