Process sequencing and process clustering in process planning using state space search

Process sequencing, as a very important part of process planning, has been the subject of many research reports in the area of process planning, but is usually treated as a feature-sequencing problem. This paper presents a novel algorithm for process sequencing, which considers the feature precedence network, different process candidates, and machine and tool constraints. The algorithm consists of two parts: process clustering and process sequencing. For clustering we used a notion of the same resource usage for different features, while for sequencing we applied the best-first search method algorithm to generate an optimal process sequence. The algorithm has been applied on several examples with realistic complexities, and it showed satisfactory results.     

Optimal non-periodic inspection scheme for a multi-component repairable system using A search algorithm

This paper proposes an approach for finding an optimal non-periodic inspection scheme on a finite time horizon for a multi-component repairable system. The system consists of several components, each of which is subjected to soft failure. Soft failures of each component do not cause the system to stop functioning, but increase the system operating costs and are detected only if inspection is performed. Thus, the system is inspected at the scheduled inspection instances and if any of its components is found to have failed, the failed component is minimally repaired. The system’s expected total cost associated with a given inspection scheme includes inspection costs, repair costs, and the penalty costs that are incurred due to the time delay between the actual occurrence of a soft failure of the components and its detection at an inspection. The objective is to determine the optimal inspection scheme which minimizes system’s expected total cost.     

Detection of spatio-temporal conflicts on a temporal 3D space system

It is critical to detect the spatio-temporal conflicts in a project schedule, since many construction conflicts occur due to constraints in construction space and unavailability of intermediate functions of the in-progress building. This paper introduces a temporal 3D space system modelling method using a COmponent State network CEntric Model (COSCEM) to integrate such project aspects as product, process, space, and intermediate functions. Based on COSCEM, a 3D CAD model can be transformed into a temporal 3D space system. The concept of ‘existence vector’ and the Boolean logic operations are defined for depicting and deriving the dynamic characteristics of project entities. The procedures for detecting spatio-temporal conflicts are also presented. A case study of moving a truck crane on an excavated access road is selected to illustrate the proposed spatio-temporal detection methodology.     

Intelligent state space pruning for Monte Carlo simulation with applications in composite power system reliability

The probabilistic reliability evaluation of composite power systems is a complicated, computation intensive, and combinatorial task. As such evaluation may suffer from issues regarding high dimensionality that lead to an increased need for computational resources, MCS is often used to evaluate the reliability of power systems. In order to alleviate this burden, an analytical method known as state space decomposition has previously been used to prune the state space that is sampled using MCS.This paper extends the state-of-the-art by proposing a novel algorithm known as intelligent state space pruning (ISSP). This algorithm leverages the intelligence of highly modified population based metaheuristic (PBM) algorithms including genetic algorithms (GA), particle swarm optimization (PSO), ant colony optimization (ACO), and artificial immune systems (AIS) to quickly, efficiently, and intelligently prune the state space that is used during MCS. The presented PBMs are modified using domain-specific knowledge to improve their performance and fine tune their intelligence. This new algorithm leads to reductions of up to 90% in total computation time and iterations required for convergence when compared to non-sequential MCS. Results are reported using the IEEE Reliability Test Systems (RTS79/MRTS).     

Queuing system evolution in a diffusion approximation scheme

An asymptotic diffusion approximation scheme is investigated as applied to the requirement evolution in semi-Markov queuing systems. In proving the diffusion approximation theorem, the compensating operator of the corresponding extended Markov process is used. This problem is solved with the help of a phase merging procedure. Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 136–145, May–June 2009. Original article submitted August 19, 2008.     

Blind Source Recovery in a State-Space Famework: Algorithms for Static and Dynamic Environments

This paper describes a generalized state space Blind Source Recovery (BSR) framework obtained by using the Kullback-Lieblar divergence as a performance functional and the application of optimization theory under the constraints of a feedforward state space structure. Update laws for both the non-linear and the linear dynamical systems have been derived for the domain of dynamic blind source recovery along both ordinary stochastic gradient and the Riemannian contra-variant gradient directions. The choice of the rich state space demixing network structure allows for the development of potent learning rules, capable of handling most filtering paradigms and convenient extension to non-linear models. Some particular filtering cases are subsequently derived from this general structure and are compared with material in the recent literature. Some of this reported work has also been implemented in dedicated hardware/software. An illustrative simulation example has been presented to demonstrate the online adaptation capabilities of the proposed algorithms.     

New control strategies for utilizing power system networks more effectively: The state of the art and the future trends based on a synthesis of the work in the cigre study committee 38

CIGRÉ Study Committee 38 deals with power system analysis and techniques. This paper gives the current status of the work in relation to making networks more effective. New equipment and new principles for system control are mentioned, as well as new concepts for investigating system reliability. The purpose is to define strategies for making networks more effective in the future.