Throughout the process industry, the conservation and allocation of mass and energy resources plays a pivotal role in the site wide optimization of a plant. Typically, raw materials are transformed into products, byproducts and wastes through pathways involving heating/cooling, pressure changes, mixing, reactions and separations. These pathways often require the addition or removal of energy from the system. The optimal management of such a system therefore requires conserving resources through the appropriate allocation of materials and energy. In a typical plant, there are both mass and energy objectives that require optimization. This dissertation will focus on optimizing the mass and energy resources present in a utility system. This will entail developing a novel framework of techniques to: target and design steam cogeneration networks while minimizing fuel requirements, identifying and utilizing sources of waste heat and incorporating heat pipes to enhance heat exchange networks. Additionally, a specific case of waste recovery will be examined when properties are the primary concern.

Throughout the process industry, the conservation and allocation of mass and energy resources plays a pivotal role in the site wide optimization of a plant. Typically, raw materials are transformed into products, byproducts and wastes through pathways involving heating/cooling, pressure changes, mixing, reactions and separations. These pathways often require the addition or removal of energy from the system. The optimal management of such a system therefore requires conserving resources through the appropriate allocation of materials and energy. In a typical plant, there are both mass and energy objectives that require optimization. This dissertation will focus on optimizing the mass and energy resources present in a utility system. This will entail developing a novel framework of techniques to: target and design steam cogeneration networks while minimizing fuel requirements, identifying and utilizing sources of waste heat and incorporating heat pipes to enhance heat exchange networks. Additionally, a specific case of waste recovery will be examined when properties are the primary concern.

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This thesis study focuses on the development of model-based optimization strategies for the integration of process scheduling and dynamic optimization, and applications of the integrated approaches to industrial polymerization processes. The integrated decision making approaches seek to explore the synergy between production schedule design and process unit control to improve process performance. The integration problem has received much attention from both the academia and industry since the past decade. For scheduling, we adopt two formulation approaches based on the state equipment network and resource task network, respectively. For dynamic optimization, we rely on the simultaneous collocation strategy to discretize the differential-algebraic equations. Two integrated formulations are proposed that result in mixed discrete/dynamic models, and solution methods based on decomposition approaches are addressed. A class of ring-opening polymerization processes are used for our industrial case studies. We develop rigorous dynamic reactor models for both semi-batch homopolymerization and copolymerization operations. The reactor models are based on first-principles such as mass and heat balances, reaction kinetics and vapor-liquid equilibria. We derive reactor models with both the population balance method and method of moments. The obtained reactor models are validated using historical plant data. Polymerization recipes are optimized with dynamic optimization algorithms to reduce polymerization times by modifying operating conditions such as the reactor temperature and monomer feed rates over time. Next, we study scheduling methods that involve multiple process units and products. The resource task network scheduling model is reformulated to the state space form that offers a good platform for incorporating dynamic models. Lastly for the integration study, we investigate a process with two parallel polymerization reactors and downstream storage and purification units. The dynamic behaviors of the two reactors are coupled through shared cooling resources. We formulate the integration problem by combining the state space resource task network model with the moment reactor model. The case study results indicate promising improvements of process performances by applying dynamic optimization and scheduling optimization separately, and more importantly, the integration of the two.

This thesis describes the design optimization of two different types of vessels. They are LHA(R), a replacement for the US Navy amphibious assault ship and DDG51, a destroyer class vessel. The overall measure of effectiveness (OMOE) and the lead ship acquisition cost (LCA) are considered to be the objective functions. The evaluation of feasibility of the designs and various ship parameter calculations are performed using the US Navy ship design evaluation software ASSET. ASSET is integrated with the design optimization software DARWIN to obtain results representing the best designs over a range of LCA. Model Center software is used to integrate the processes ASSET and Darwin. The results generated will provide the owner with the best designs possible (designs with high OMOE) over a range of LCA. This thesis is mainly of academic interest. The results generated could help the owners to look at various design options available for the amount of money they are willing to spend. / Master of Science

Business Administration, Business Process & Supply Chain Management, Degree Project (Master), 30 higher education credits, 5FE02E, Spring 2012   Authors: Kateryna Zubova and Olga Arikainen   Tutor: Åsa Gustavsson Title: Procurement Process Integration in Swedish and Ukrainian Companies Producing Machinery and Equipment Background: Although the science of economics and logistics comprises a great amount of literature on supply chain integration, there is a lack of information on procurement process integration. Procurement process is one the supply chain processes and is one of the most important processes for manufacturing companies. Purpose: To describe the level of procurement process integration (PPI), tools of PPI and barriers to PPI from buyers’ perspective in Swedish and Ukrainian companies producing machinery and equipment, and then to test if there is a significant difference in them between respondents of two countries. Method: Web-based questionnaire was created and sent out to 500 companies producing machinery and equipment in Sweden and to 500 companies in Ukraine.  73 responses were received from Swedish companies and 49 responses from Ukrainian companies. T-test was performed in order to test the differences in procurement process integration between Swedish and Ukrainian companies in terms of levels of integration, tools of integration and barriers to integration. Results, conclusions: There is no significant difference in the level of integration between Swedish and Ukrainian companies. In both countries the average level of integration is medium that means long-term relationships which are reviewed periodically. However, significant differences were found in the tools and barriers to procurement process integration between Swedish and Ukrainian companies.

Much research in the area of process integration has focused on steady-state processes. However, there are many process units that are inherently unsteady-state or perform best when operated in an unsteady-state manner. Unsteady-state units are vital to chemical processes but are unable to be included in current process optimization methods. Previous methods to optimize processes containing unsteady-state units place restrictions or constraints on their use. This optimization still does not give the best system design because the solution found will only be the best out of the available options which likely excludes the true optimal design. To remedy this, a methodology was created to incorporate unsteady-state process units into process optimization analysis. This methodology is as general as possible. Unlike many existing unsteadystate optimization methods, it determines all three main components of process design: the network configuration, sizes of units, and operation schedule. This generality ensures that the truly optimal process design will be found. Three problems were solved to illustrate the solution methodology. First, a general mass exchange network was optimized. The optimization formulation resulted in a mixed-integer nonlinear program, and linearization techniques were used to find the global solution. A property interception network was also optimized, the first work done using property integration for systems with unsteady-state behavior. Finally, an industrial semi-batch water purification system was optimized. This problem showed how process integration could be used to optimize a hybrid system and gain insights into the process under many different operating conditions.

With the escalating levels of water demand, there is a need for expansion in the capacity of water desalination infrastructure and for better management and distribution of water resources. This dissertation introduces a systems approach to the optimization of macroscopic water desalination and distribution networks to tackle three problems: 1. Optimal design of desalination and allocation networks for a given demand, 2. Optimal operation of an existing infrastructure of water desalination, distribution, and storage, 3.Optimal planning for expanding the capacity of desalination plants to meet an increasing water demand over a time horizon. A source-interception-sink representation was developed to embed potential configurations of interest. Mathematical programming was used to model the problem by studying different objective functions while accounting for constraints the supply, demand, mass conservation, technical performance, and economic aspects. Such approach determines the type of technologies to be selected, the location and capacity of the desalination plants, and the distribution of the desalinated water from sources to destinations. For the operation and planning problems, the planning horizon was discretized into periods and a multi-period optimization approach was adopted with decisions made for each period. Short- and long-term water storage options (e.g., in storage tanks, aquifers) were included in the optimization approach. Water recycle/reuse was enhanced via the use of treated water and its utilization was improved by minimizing the losses observed in discharged water resulting from the linkage of power plants and thermal desalination plants and the lack of integration between water production and consumption. Several case studies were solved to demonstrate the applicability of the devised approaches.

Abstract ¡@¡@In this era of knowledge-based economy, the environment is changing fast. The continuous progress of information technology plays the important role for putting knowledge-based management into practice. On the other hand, because of appearance of knowledge-based management, persons gradually realize it become harder to produce concrete result by person¡¦s knowledge and effort. Members of organization, Nowadays, must use teamwork to gain organizational-knowledge and through communication & coordination between teams and members to finish tasks for achieving enterprise¡¦s goal. ¡@¡@This research is using the concept and the method of knowledge-based management and process management to build up organization and process design for achieving the strategy goal of enterprise. It also explores how to find adequate knowledge through information technology in the shortest time and transform the knowledge into the reliable organizational-knowledge by sharing and applying. In addition, the topics of the research include linking engineering knowledge and organizational form from a clear goal of technology strategy according to the point of view of system process integration. Under the process structure of the research, we seek and evaluate key indexes of affecting performance to develop the ability of fast developing new technology and new process. And intend to expedite organization toward creating knowledge developing related to enterprise¡¦s strategies in order to get better competitive edge.

In our daily lives, people constantly need to schedule their activities to meet their personal goals. Many of these activities involve the interaction with organization sectors, which must follow certain regulations in terms of input data, doable time and places. These regulations form personal processes. In previous work, [Chen01] proposed a personal process model that define a personal process as a set of tasks and a coordination on the tasks and a personal workflow system architecture. However, the proposed system is solely to facilitate a mobile user in deciding when, where, and how to process a task. We have noticed that many processes initiated by an individual often involve business processes coming from different organizations. Our objective in this thesis is to revise the personal process model proposed in [Chen01] by incorporating business processes existing in different sectors, developing a simpler query method, and extending personal workflow architecture in support of the new model. In our architecture, the management of personal processes involves three parties: the service provider, the template provider and the PWFMS. The service providers supply personal processes, each of which enable users to achieve a specific goal, and keep track of the status of executed tasks. The template providers incorporate several personal processes from different service providers and form a useful template for a user. The PWFMSs assist users in managing personal processes. In order to prove our idea, we implemented a prototype of the architecture.