A localização de fábricas, fornecedores e/ou CDs é um problema de grande complexidade, principalmente em empresas com operações internacionais. Na literatura mundial são poucos os modelos desenvolvidos que tratam da localização de instalações em escala global. Este trabalho propõe um modelo de Programação Linear Inteira Mista que soluciona o problema minimizando os custos logísticos (custos fixos, custos de transferência, custos de distribuição, impostos não recuperáveis, estoques, take-or-pay, matéria-prima e custos de agregação de valor e transbordo) levando em consideração vários elos da cadeia de suprimentos. Como principais contribuições do modelo citam-se a inclusão de benefícios fiscais em transações internacionais, tais como o drawback, o cálculo pioneiro para custo no carregamento dos estoques e o tratamento dado aos custos tipo take-or-pay. São sugeridas adaptações do modelo para utilização em quaisquer segmentos de indústria. O modelo foi aplicado com sucesso em um caso real de uma indústria do segmento químico. / The location of factories, suppliers and distribution centers has always been a problem of great complexity, mainly for companies with global operations. In the literature, there are a few models developed for facilities location in a global scale. This work proposes a Mixed Integer Linear Programming model that solves the problem minimizing the total logistic cost (fixed, transfer and distribution costs, non recoverable duties, carrying, take-or-pay, raw material, added value and handling costs) taking into consideration several echelons in the supply chain network. The main contributions of the proposed model are the considerations regarding fiscal benefits in international trade such as drawback, the pioneer carrying cost calculation and the treatment given to the take-or-pay costs. Some adaptations of the model have been suggested for use in any type of industry. The model was successfully applied in a real case of a chemical industry.

<p>U disertaciji je predstavljen pristup zasnovan na algoritmu mešovitog celobrojnog linearnog programiranja (MILP) za određivanje optimalnog broja, tipa i lokacije uređaja za automatizaciju distributivne mreže. Ugradnja različitih tipova nove opreme (daljinski kontrolisani reklozeri, sekcioneri i indikatori prolaska struje kvara) kao i relokacija postojeće opreme su istovremeno razmatrani. Prilikom određivanja optimalnog scenarija za automatizaciju, predloženi pristup uvažava troškove ispada potrošača/proizvođača usled trenutnih, kratkotrajnih i dugotrajnih ispada, najčešće korišćene pokazatelje pouzdanosti (SAIFI, SAIDI, MAIFI, i ASIDI) kao i troškove distributivnog preduzeća, asocirane uređajima za automatizaciju i ekipama koje su uključene u proces rešavanja prekida napajanja.<br />Dakle, osnovni cilj ove disertacije je, da se napravi model zasnovan na mešovitom celobrojnom linearnom programiranju koji će omogućiti određivanje najboljeg scenarija za automatizaciju distributivne mreže u slučajevima kada se ocena kvaliteta isporuke definiše preko pokazatelja pouzdanosti, preko troškova usled prekida napajanja ili kombinacijom ova dva pokazatelja.</p> / <p>The dissertation presents a mixed integer linear programming (MILP) based approach for determining the optimal number, type and location of automation devices to be installed in the network by considering different types of devices simultaneously (remotely controlled circuit breakers/reclosers, sectionalizing switches, remotely supervised fault passage indicators). Simultaneously, it determines the new (optimal) locations of the automation devices that already exist in the network. In determining the most effective network automation scenario, the proposed approach takes into account the outage cost of consumers/producers due to momentary, short-term, and long-term interruptions, the commonly used network reliability indices (SAIFI, SAIDI, MAIFI, and ASIDI) as well as the cost of automation devices and the cost of crews. It provides the best network automation scenario in distribution systems if the network reliability indices are used for measuring the distribution system reliability, if cost of interruptions is defined to all consumers/producers, and if both approaches (criteria) are used.</p>

<p>Energy management has become a major concern in the past two decades with the increasing energy prices, overutilization of natural resources and increased carbon emissions. According to the department of Energy the industrial sector solely consumes 22.4% of the energy produced in the country [1]. This calls for an urgent need for the industries to design and implement energy efficient practices by analyzing the energy consumption, electricity data and making use of energy efficient equipment. Although, utility companies are providing incentives to consumer participating in Demand Response programs, there isn’t an active implementation of energy management principles from the consumer’s side. Technological advancements in controls, automation, optimization and big data can be harnessed to achieve this which in other words is referred to as “Smart Manufacturing”. In this research energy management techniques have been designed for two SEU (Significant Energy Use) equipment HVAC systems, Compressors and load shifting in manufacturing environments using control and optimization.</p> <p>The addressed energy management techniques associated with each of the SEUs are very generic in nature which make them applicable for most of the industries. Firstly, the loads or the energy consuming equipment has been categorized into flexible and non-flexible loads based on their priority level and flexibility in running schedule. For the flexible loads, an optimal load scheduler has been modelled using Mixed Integer Linear Programming (MILP) method that find carries out load shifting by using the predicted demand of the rest of the plant and scheduling the loads during the low demand periods. The cases of interruptible loads and non-interruptible have been solved to demonstrate load shifting. This essentially resulted in lowering the peak demand and hence cost savings for both “Time-of-Use” and Demand based price schemes. </p> <p>The compressor load sharing problem was next considered for optimal distribution of loads among VFD equipped compressors running in parallel to meet the demand. The model is based on MILP problem and case studies was carried out for heavy duty (>10HP) and light duty compressors (<=10HP). Using the compressor scheduler, there was about 16% energy and cost saving for the light duty compressors and 14.6% for the heavy duty compressors</p> <p>HVAC systems being one of the major energy consumer in manufacturing industries was modelled using the generic lumped parameter method. An Electroplating facility named Electro-Spec was modelled in Simulink and was validated using the real data that was collected from the facility. The Mean Absolute Error (MAE) was about 0.39 for the model which is suitable for implementing controllers for the purpose of energy management. MATLAB and Simulink were used to design and implement the state-of-the-art Model Predictive Control for the purpose of energy efficient control. The MPC was chosen due to its ability to easily handle Multi Input Multi Output Systems, system constraints and its optimal nature. The MPC resulted in a temperature response with a rise time of 10 minutes and a steady state error of less than 0.001. Also from the input response, it was observed that the MPC provided just enough input for the temperature to stay at the set point and as a result led to about 27.6% energy and cost savings. Thus this research has a potential of energy and cost savings and can be readily applied to most of the manufacturing industries that use HVAC, Compressors and machines as their primary energy consumer.</p><br>

In this research, a decision support model for coordinating sustainable product and supply chain design decisions is developed using a multi-stage hierarchical approach. The model evaluates alternate product designs and their corresponding supply chain configurations to identify the best product design and the corresponding supply chain configuration that maximizes the economic, environmental and societal benefits. The model considers a total life-cycle approach and incorporates closed-loop flow among multiple product lifecycles. In the first stage, a mixed integer linear programming model is developed to select for each product design an optimal supply chain configuration that maximizes the profit. In the subsequent stages, the economic, environmental and societal multiple life-cycle analysis models are developed which assess the economic, environment and the societal performance of each product design and its optimal supply chain configuration to identify the best product design with highest sustainability benefits. The decision support model is applied for an example problem to illustrate the procedure for identifying the best sustainable design. Later, the model is applied for a real-time refrigerator case to identify the best refrigerator design that maximizes economic, environmental and societal benefits. Further, sensitivity analysis is performed on the optimization model to study the closed-loop supply chain behavior under various situations. The results indicated that both product and supply chain design criteria significantly influence the performance of the supply chain. The results provided insights into closed-loop supply chain models and their behavior under various situations. Decision support models such as above can help a company identify the best designs that bring highest sustainability benefits, can provide a manager with holistic view and the impact of their design decisions on the supply chain performance and also provide areas for improvement.

A localização de fábricas, fornecedores e/ou CDs é um problema de grande complexidade, principalmente em empresas com operações internacionais. Na literatura mundial são poucos os modelos desenvolvidos que tratam da localização de instalações em escala global. Este trabalho propõe um modelo de Programação Linear Inteira Mista que soluciona o problema minimizando os custos logísticos (custos fixos, custos de transferência, custos de distribuição, impostos não recuperáveis, estoques, take-or-pay, matéria-prima e custos de agregação de valor e transbordo) levando em consideração vários elos da cadeia de suprimentos. Como principais contribuições do modelo citam-se a inclusão de benefícios fiscais em transações internacionais, tais como o drawback, o cálculo pioneiro para custo no carregamento dos estoques e o tratamento dado aos custos tipo take-or-pay. São sugeridas adaptações do modelo para utilização em quaisquer segmentos de indústria. O modelo foi aplicado com sucesso em um caso real de uma indústria do segmento químico. / The location of factories, suppliers and distribution centers has always been a problem of great complexity, mainly for companies with global operations. In the literature, there are a few models developed for facilities location in a global scale. This work proposes a Mixed Integer Linear Programming model that solves the problem minimizing the total logistic cost (fixed, transfer and distribution costs, non recoverable duties, carrying, take-or-pay, raw material, added value and handling costs) taking into consideration several echelons in the supply chain network. The main contributions of the proposed model are the considerations regarding fiscal benefits in international trade such as drawback, the pioneer carrying cost calculation and the treatment given to the take-or-pay costs. Some adaptations of the model have been suggested for use in any type of industry. The model was successfully applied in a real case of a chemical industry.

Este trabalho trata de um problema de programação da produção em fundições de pequeno porte, que consiste em programar as ligas que devem ser produzidas em cada período do planejamento e como tais ligas devem ser usadas para a produção de itens sob encomenda, de modo que atrasos e custos operacionais sejam minimizados. Devido à certa incerteza nos dados do problema, a estratégia de horizonte rolante foi empregada. Este problema é representado por um modelo matemático de programação linear inteira mista. Neste trabalho foi desenvolvida uma heurística do tipo residual para obter uma boa solução inteira factível do problema, partindo da solução contínua encontrada pelos métodos relaxe-e-fixe e busca local / This work addresses a planning production problem that arises in small market-driven foundries, which consists of programming a number of alloys that have to be produced in each period of the planning horizon and how these alloys should be used to producing ordered items, in such way that delays and operational costs are minimized. Due to uncertainties in the problem data, the strategy of rolling horizon was used. This problem is modeled as a mixed integer linear programe. In this work we developed a residual typed heuristic in order to obtain a good feasible integer solution of the problem, which are built from the continuous solution found by relax-and-fix and local search methods. Keywords: Lot-sizing problems, mixed integer linear programming, production planning in foundries

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The scheduling of the converter aisle of a nickel smelting plant is a non-trivial task with significant consequences to plant profitability and production. An optimization-based scheduling formulation is developed using a continuous-time paradigm to accurately represent event timings. The formulation accounts for environmental restrictions on sulfur dioxide emissions using event timing constraints. The formulation includes novel semi-continuous modeling to represent flash furnaces which operate with a continuous inlet flow and intermittent discrete material removal, as well as, a novel sequencing and symmetry-breaking scheme to account for identical units operating in parallel. A rolling horizon feature is included in the formulation to accommodate multi-period optimization. Tightening constraints are developed and used to improve the computational performance of the optimization and demonstrate the capacity of the proposed methodology to function as a real-time decision-support tool. A solution procedure is presented where an aggregate model is used to bound the objective function of the master problem in a two layer optimization scheme. Finally, a novel multi-tiered procedure is presented to enhance the optimization solution by re-optimizing for objectives of decreasing priority in order to minimize task start times and penalize deviations in the furnace flow rate. To address the closed-loop properties of scheduling, a reactive scheduling mechanism is included to allow for rescheduling to account the impact of process disturbances on the operating schedule. A methodology for reducing radical scheduling changes due to the optimization during reactive scheduling is presented. The reactive scheduling algorithm utilizes a tiered optimization approach that progressively increases the degrees of freedom available, as required, in order to achieve a feasible production schedule. The use of the reactive scheduling algorithm demonstrates the ability to reject disturbances and transition plant operation in an agile manner. / Thesis / Master of Applied Science (MASc)

Additional electricity meters behind the grid access point can improve understanding of energy consumption patterns and thus, adjust consumption behavior. For this study, smart meters were installed in three hostels, out of which two are analyzed further in this paper. Starting from an onsite inspection, all appliances were assigned to reasonable groups for sub-metering. Based on data for the year 2021, the sites are characterized according to the sub-metering concept. In addition, load profiles for type-days are derived, which allows to establish a baseload during COVID lockdown and compare it to consumption patterns for normal occupation. In the prescriptive part, the demand profiles are analyzed regarding their economic potential for load shifting. Consumption data for one week with normal occupation is used as input for techno-economic modeling. The mixed-integer model minimizes electricity purchasing costs for different scenarios including dynamic tariffs and onsite generation from photovoltaics.

This study derives the levelized cost of heat (LCOH) for exemplary post-fossil district heating (DH) scenarios. The DH system of Leipzig in 2040 under the assumption of a completely climate-neutral heat supply is considered. Accordingly, four generation scenarios (GS) are proposed based on different energy carriers that are characterized as follows: (1) natural gas with carbon capture and storage, (2) hydrogen, (3) diversified mix of biomass, waste heat and solar, and (4) electricity. In addition, the scenarios’ robustness toward commodity prices is investigated using a sensitivity analysis. A modeling environment was used to optimize the hourly economic dispatch. Based on this, levelized costs are determined. For the reference case, the LCOH of the GS 1 and 2 exceeds the LCOH of GS 3 and 4. Furthermore, the results indicate that relying on singular energy carriers as opposed to diversified generation portfolios leads to less robust LCOH regarding price sensitivities.