The introduction of a new product into an operating factory can have significant adverse impacts on the throughput and cycle time of all products produced in the factory, and thus needs to be managed carefully. In pre...
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The introduction of a new product into an operating factory can have significant adverse impacts on the throughput and cycle time of all products produced in the factory, and thus needs to be managed carefully. In previous work we proposed a production planning model for new product introductions that captures the impact of additional variability caused by the new product and of learning as experience producing the new product is gained. This paper extends the earlier work by incorporating learning through deliberate experimentation using engineering lots and the impact of cycle time on line yield due to delays in detecting adverse events. We formulate a non-convex nonlinear optimization model to determine the mix of production and engineering lots to be processed, and obtain approximate solutions using a genetic algorithm. Numerical experiments with different scenarios show the importance of carefully managing the releases of production and engineering lots and of accelerating learning early in the time horizon through judicious use of engineering lots.
Inter-area oscillations and cascading failures are the most serious threats to the security of the electric power system. Uncontrolled islanding will occur in the event of an unstable inter-area oscillation or a progr...
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Inter-area oscillations and cascading failures are the most serious threats to the security of the electric power system. Uncontrolled islanding will occur in the event of an unstable inter-area oscillation or a progressive cascading failure. The establishment of uncontrolled islands with a deficiency in load-generation balance is the main reason for system blackout. Controlled islanding has been proposed as a preventive strategy for reducing the risk of blackout in this regard. A new algorithm for applying the controlled islanding strategy is proposed in this paper, based on load coherency and nearest electrical distances between coherent groups of generators. Coherent generators as the main core for controlled islands are identified in this method, which is based on the correlation coefficients between generators and the DBSCAN clustering algorithm. The sub-networks are then created by applying mixed-integer linearprogramming to each coherent group. Once this is accomplished, non-linear programming is used to construct the stable sub-networks associated with islands that meet the requirements of load-generation balance, voltage limitations, and transmission limits. The proposed scheme is implemented on the small-scale IEEE 39-bus system and a large-scale realistic power system which is the Iran power grid. The results demonstrate that the proposed method is capable of being implemented in a real power system.
Problems with robot dress packs are a major reason for on-line adjustments of robot programs and down-time in robot stations. It is therefore of high value if the physical behaviour of the dress packs can be considere...
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Problems with robot dress packs are a major reason for on-line adjustments of robot programs and down-time in robot stations. It is therefore of high value if the physical behaviour of the dress packs can be considered with simulation methods already during the off-line programming process for a robot station. This paper presents a method for quasi-static path optimization for an industrial robot with respect to its deformable dress pack. Given an initial collision-free path generated by an automatic path planner, the via point configurations of the path are optimized with respect to the performance aspects of the dress pack. The method is derived from a general framework for parameter optimization of a mechanical system subject to quasi-static motions and deformations. The optimal parameter values are obtained from numerical solutions to a non-linear programming problem in which the static equilibrium equations of the system hold at discrete times. Due to the large-scale nature of this problem, a dress pack is modelled as a discrete Cosserat rod, which is the preferred choice for modeling large spatial deformations of a slender flexible structure with coarse discretization. The method is applied to an industrial robot moving in-between stud welding operations in a stud welding station. The optimized path reduces the stress in the dress pack and keeps the dressed robot from the surrounding geometry with a prescribed safety clearance during the entire robot motion.
In this work, we perform a two-stage design optimization of the folded beam multi-resonant piezoelectric energy harvester. The optimization routine involves a global pre-optimization using evolutionary algorithm and a...
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In this work, we perform a two-stage design optimization of the folded beam multi-resonant piezoelectric energy harvester. The optimization routine involves a global pre-optimization using evolutionary algorithm and a subsequent local optimization by classical non-linear programming. Optimization resulted in designs, which shows promising characteristics in simulation. For the validation of simulation results, we fabricated the optimal designs and performed experimental characterization. Simultaneously, we developed a comparable array of single beam piezoelectric harvesters, which we compared with the optimized folded beam designs. Both new designs significantly outperform the initial one in terms of frequency spacing. Furthermore, the experimental data demonstrate that the optimized folded beam designs generate considerably higher maximum voltage compared to the proposed array-structured designs.
Though not as comprehensive as Zarchan(1) for example, it is not intended to compete with books covering state-of-the-art guidance and control strategies, but rather to provide an overview of the missile systems and d...
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Though not as comprehensive as Zarchan(1) for example, it is not intended to compete with books covering state-of-the-art guidance and control strategies, but rather to provide an overview of the missile systems and design processes that must be considered, culminating in an exploration of the ubiquitous proportional navigation guidance strategy.
[...]in chapter 8, we reach PN and extended PN guidance laws.
[...]the optimal trajectory control is formed as a non-linear program with initial and terminal constraints whose solution is proposed via the transcription method (although not explained as such in the text).
In the last 60 years, remanufacturing has evolved as the major way for recovering value from products or components of the product, because the remanufactured product or component is not only cheaper than those obtain...
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In the last 60 years, remanufacturing has evolved as the major way for recovering value from products or components of the product, because the remanufactured product or component is not only cheaper than those obtained from conventional sources of manufacturing and/or purchasing, but the outputs are also "good-as-new". The automobile sector, in particular, has seen predominant remanufacturing. Given the benefits of remanufacturing, this study proposes a new prospective business approach, particularly for the Indian automobile sector by introducing component remanufacturing. Particularly this study considers Multiple Products (MP) that are assembled by proposing Component Remanufacturing (CR) as a new source along with regular manufacturing and purchasing sources for components. In addition, this study considers the complexities of "Backordering (BO)" along with a new proposal for "Product Substitution (PS)" option to satisfy demand. Hence, the research problem considered in this study is referred as "MP-CR problem with BO&PS". For this complex and new problem, the study empirically demonstrates that the MP-CR problem with BO&PS is a new prospective profitable business approach in comparison with the existing "Multi Products problem with Backordering (MP problem with BO)" for an Indian automobile OEM, by proposing a mathematical model with the objective of profit maximization.
This paper presents an approach to include security constraints in the Optimal Power Flow (OPF) problem aiming at providing a power system operation in safe region. The proposed operating region is formed by elliptica...
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This paper presents an approach to include security constraints in the Optimal Power Flow (OPF) problem aiming at providing a power system operation in safe region. The proposed operating region is formed by elliptical wraps that enclose historical and safe system operative states, which include wind power generation and demand scenarios. The wraps are obtained through a proposed non-linear programming (NLP) problem that defines the ellipse's shape by using nodal voltages at buses of interest. In addition, the proposed approach can determine the operational risk, that is, the risk of an operative state leaving the safety region, by applying a relaxation method. The proposed methodology is tested in the 39-bus New England system and 118-bus IEEE test system. The results show that the elliptical wraps are effective to enclose the secure operational states and maintain the system within a safe region.
Intrusion detection system is a second layer of defence in a secured network environment. When comes to an IoT platform, the role of IDS is very critical since it is highly vulnerable to security threats. For a trustw...
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Intrusion detection system is a second layer of defence in a secured network environment. When comes to an IoT platform, the role of IDS is very critical since it is highly vulnerable to security threats. For a trustworthy intrusion detection system in a network, it is necessary to improve the true positives with minimum false positives. Research reveals that the true positive and false positive are conflicting objectives that are to be simultaneously optimized and hence their trade-off always exists as a major challenge. This paper presents a method to solve the tradeoff among these conflicting objectives using multi-objective particle swarm optimization approach. We conducted empirical analysis of the system with multiple machine learning classifiers. Experimental results reveals that this technique with J48 classifier gives the highest gbest value 10.77 with minimum optimum value of false positive 0.02 and maximum true positive 0.995. Empirical evaluation shows an incredible improvement in Pareto set in the objective function space by attaining an optimum point.
Given the large amount of energy required in the building sector, an interesting opportunity to reach future sustainable energy systems is the path towards low energy buildings. This work proposes an approach for opti...
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Given the large amount of energy required in the building sector, an interesting opportunity to reach future sustainable energy systems is the path towards low energy buildings. This work proposes an approach for optimally integrating building-scale energy technologies (both traditional and renewable) to enhance the transformation of the existing buildings (often energetically inefficient) in low-carbon systems. The approach promotes a transition sustainable from both the economic and environmental perspectives. Both operation and design optimization are considered with the aim of suggesting the best set of capacity of the technologies to be installed taking into account the expected operations. The building-scale technologies are integrated with proper storage units: Li-ion batteries and thermal storage (latent heat, that requires low installation space). As a dispatchable renewable technology, a biogas small-scale combined heat and power unit is included in the system. Once the key role played by this component in meeting the loads is proved, an analysis of the impact of the cost of the primary energy carrier of this technology on the system design is carried out. Two optimization approaches have been adopted (both based on non-linear programming). Results show that operation costs can be reduced by up to 29%. The adoption of a combined approach that takes into account both operation and design optimization lead to a reduction in installation and operating costs by up to 27%. In the analyzed cases, the use of the combined optimization confirms that latent heat storage is more suitable to be installed than electric storage (about -4.5% cost).
The increasing presence of renewable distributed generation (DG) units such as photovoltaic and wind power generation is a major challenge for the suitable operation of the electrical distribution systems (EDSs). Unce...
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The increasing presence of renewable distributed generation (DG) units such as photovoltaic and wind power generation is a major challenge for the suitable operation of the electrical distribution systems (EDSs). Uncertainties of renewable DG units and loads, related to the stochastic nature of solar irradiation, wind speed, and consumer behavior, require efficient tools that help the distribution system operator to properly define a control plan of the EDS. Within this framework, the probabilistic optimal power flow (POPF) provides statistical information(e.g. voltage profile, power flows, and power losses) according to the variation of the stochastic variables (e.g. power demand and injection of generation units). Many available POPF methods have been designed for transmission systems and/or are based on Monte Carlo simulation (MCS), which requires a high computational effort. On the other hand, other approaches adopt analytical methods, which are not applied considering the characteristics of distribution systems. This paper proposes a fast-specialized point estimate method for the POPF in EDSs with the presence of renewable DG units, based on a linearization of the Branch Flow equations and Hong's point estimate method. Due to its convex nature, the advantage of the proposed method is to use wellestablished linearprogramming commercial solvers to solve the problem. Numerical results using the IEEE 69-bus and a real EDS demonstrate the efficiency in terms of computational burden and accuracy of the proposed method compared to MCS and Cumulant approaches.
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