Multiple Performance Indices Research Articles

The use of the Taguchi method and principal component analysis for the sensitivity analysis of a dual-purpose six-bar mechanism

In this paper, the Taguchi method and the principal component analysis were applied to a dual-purpose six-bar mechanism for investigating the influence of manufacturing tolerance and joint clearance on the quality of the mechanism. Experiments were carried out based on the orthogonal array from the Taguchi method, which calculated the S/ N ratios of the positional and angular errors of a dual-purpose six-bar mechanism. Using the principal component analysis, the S/ N ratios were transformed into a multiple performance index to further understand the effect of the control factors on the quality of the six-bar mechanism. Using the analysis of response table and response diagram, the key dimensions of the mechanism could be identified and their tolerance optimized, i.e. decreasing the tolerance of important dimensions and increasing the rest, with the objective of simultaneously improving the quality of the mechanism and reducing the cost.

Grey relational analysis coupled with principal component analysis for optimization design of the cutting parameters in high-speed end milling

This paper investigates optimization design of the cutting parameters for rough cutting processes in high-speed end milling on SKD61 tool steel. The major characteristics indexes for performance selected to evaluate the processes are tool life and metal removal rate, and the corresponding cutting parameters are milling type, spindle speed, feed per tooth, radial depth of cut, and axial depth of cut. In this study, the process is intrinsically with multiple performance indexes so that grey relational analysis that uses grey relational grade as performance index is specially adopted to determine the optimal combination of cutting parameters. Moreover, the principal component analysis is applied to evaluate the weighting values corresponding to various performance characteristics so that their relative importance can be properly and objectively described. The results of confirmation experiments reveal that grey relational analysis coupled with principal component analysis can effectively acquire the optimal combination of cutting parameters. Hence, this confirms that the proposed approach in this study can be an useful tool to improve the cutting performance of rough cutting processes in high-speed end milling process.

Performance measurement for accountability in corporate governance

PurposeThe purpose of this paper is to show the applicability of data envelopment analysis (DEA) in arriving at an unbiased account of relative performance in a set of companies, using the pharmaceutical industry as an example.Design/methodology/approachA DEA‐based income efficiency measure of business performance for the pharmaceutical industry is computed. The pharmaceutical industry, which includes many multinational corporations with complex governance problems, and the strategies that allowed firm efficiency rankings to change over time, over ten recent years, are analyzed.FindingsThe analyses indicate that the inclines and declines in DEA efficiency rankings are related to the strategic choices made by the upper management.Research limitations/implicationsThe paper attempted to trace firm behavior post hoc to validate the DEA rankings. All relevant firm behavior may not have been captured; the paper only attempted to capture behavior reported in the respectable business press, which may introduce a bias.Practical implicationsThe approach may be ideal to evaluate strategic managers (CEOs, general managers, and presidents) by board of directors, since it relates multiple performance indices to a meta‐measure of performance. Another group of beneficiaries include sector financial analysts. The approach adds a new dimension to sector analysis, to compare specific industries and identify the relative rankings of firms on multiple performance indices.Originality/valueThe paper demonstrates the usefulness of DEA in performance governance measurement by applying it to the pharmaceuticals industry.

A systematic procedure to obtain a preferable and robust ranking of units

This paper introduces one systematic procedure for the manager of an organization to assess units under its governance using multiple performance indices. The goal of this systematic procedure is to assist the manager in obtaining a preferable and robust ranking result for units. In this procedure, for all units, one common set of weights attached to the performance indices is determined in order to maximize the group's comprehensive score. Then, using the common set of weights, each unit's comprehensive score is evaluated and compared for ranking. In order to obtain the preferable ranking, the manager's subjective preference is considered and formulated by the virtual weights restrictions while determining the common weights in the procedure. The procedure is applied in order to obtain a robust ranking by modifying the boundary of the feasible region of virtual weights restrictions in each assessment. The final statistical ranking of all assessments provides the manager with one robust ranking, which is invariant in different feasible regions of virtual weights restrictions in the numerical example.

Multiple-objective scheduling and real-time dispatching for the semiconductor manufacturing system

Implementing efficient scheduling and dispatching policies is a critical means to gain competitiveness for modern semiconductor manufacturing systems. In contemporary global market, a successful semiconductor manufacturer has to excel in multiple performance indices, consequently qualified scheduling approaches should provide efficient and holistic management of wafer products, information and manufacturing resources and make adaptive decisions based on real-time processing status to reach an overall optimized system performance. To cope with this challenge, a timed extended object-oriented Petri nets (EOPNs) based multiple-objective scheduling and real-time dispatching approach is proposed in this paper. Four performance objectives pursued by semiconductor manufacturers are integrated into a priority-ranking algorithm that serves as the initial scheduling guidance, and then all wafer lots will be dynamically dispatched by the hybrid real-time dispatching control system. A set of simulation experiments validate the proposed multiple-objective scheduling and real-time dispatching algorithm may achieve satisfactory performances.

The infrastructure of the timed EOPNs-based multiple-objective real-time scheduling system for 300 mm wafer fab

Modern semiconductor wafer fabrication systems are changing from 200 mm to 300 mm wafer processing, and with the dual promises of more chips per wafer and economy of scale, leading semiconductor manufacturers are attracted to developing and implementing 300 mm wafer fabs. However, in today's dynamic and competitive global market, a successful semiconductor manufacturer has to excel in multiple performance indices, such as manufacturing cycle time and on-time delivery, and simultaneously optimize these objectives to reach the best-compromised system achievement. To cope with this challenge, in this paper, the infrastructure of a timed EOPNs-based multiple-objective real-time scheduling system (MRSS) is proposed to tackle complex 300 mm wafer fabs. Four specific performance objectives pursued by contemporary semiconductor manufacturers are integrated into a priority-ranking algorithm, which can serve as the initial scheduling guidance, and then all wafer lots will be dynamically dispatched by the real-time state-dependent dispatching system. This dispatching control system is timed EOPN-based and adopts a heterarchical organization that leads to a better real-time performance and adaptability. As the foundation of real-time schedule, the timed EOPNs modelling approach is expounded in detail, and the prototype of the MRSS simulation system is also provided.

Familiarization and Reliability of Multiple Sprint Running Performance Indices

The aims of this study were to evaluate the time-course of the familiarization process associated with a test of multiple sprint running performance and to determine the reliability of various performance indices once familiarization had been established. Eleven physically active men (mean age: 21 +/- 2 years) completed 4 multiple sprint running trials (12 x 30 m; repeated at 35-s intervals) with 7 days between trials. All testing was conducted indoors, and times were recorded by twin-beam photocells. Results revealed no apparent learning effects as evidenced by no significant (p > 0.05) between-trial differences in measures of fastest or mean 30-m sprint time. Within-subject test-retest reliability determined over 4 trials by coefficient of variation (CV) and intraclass correlation coefficient (ICC) showed excellent reliability for measures of fastest and mean sprint times (CV range: 1.34-2.24%; ICC range: 0.79-0.94). Pre- and posttrial blood lactate concentrations showed good reliability when judged in context with typical values (CV range: 12.08-18.21%; ICC range: 0.72-0.78). In contrast, and in line with previous research, fatigue data showed much greater variability (CV: 26.43%; ICC: 0.66). The results of this study suggest that high degrees of test-retest reliability can be obtained in many multiple sprint running indices without the need for prior familiarization.

Taguchi-fuzzy-based approach for the sensitivity analysis of a four-bar function generator

This article aims to use the Taguchi method coupled with fuzzy logic on the tolerance sensitivity analysis of a four-bar function generator. Experiments designed by the Taguchi method were carried out for obtaining the mean and the maximum displacement variations of the function generator. By converting these two variations into a multiple performance index by means of fuzzy logic, the effect of each control factor on the mechanism quality was further analysed. The Taguchi method coupled with fuzzy logic was used to systematically analyse the effect of individual control factors on the displacement variations of a four-bar function generator from which the key dimensions were identified.

Integrated control of automotive electrical power steering and active suspension systems based on random sub-optimal control

This paper addresses the problem of integrated control of electrical power steering systems (EPS) and active suspension systems (ASS). Through integrating EPS with ASS, a full car dynamic model is established. Based on the integrated model, a random sub-optimal control strategy based on output feedback is designed to fulfil the integrated control of both EPS and ASS. The characteristics of the integrated control system are analysed using Matlab/Simulink and a series of comparisons are made with the system without control and the ASS-only/EPS-only system. The simulation results show that the integrated control scheme can not only enhance the steering quality, but also significantly isolate the road excitation. Moreover, the integrated control system has a great improvement on anti-roll and anti-pitch abilities. The proposed research provides a theoretical solution for simultaneously improving the multiple vehicle performance indices including manoeuvrability, handling stability, ride comfort, and safety.

THE USE OF FUZZY LOGIC IN THE TAGUCHI METHOD FOR THE DETERMINATION OF THE TOLERANCE OF A SIX-BAR HINGE MECHANISM

In this paper fuzzy logic was applied to the Taguchi method to design the dimensional tolerances of a six-bar hinge mechanism with multiple performance characteristics (MPC). A fuzzy logic system was used to determine the relationship between the S/N (signal to noise) ratios of the position and the angle error for assessing the level of importance of each control factor in the hinge mechanism. The contribution of each control factor to the variations was also quantified through the response table and response diagram and the key dimensions found to significantly affect the quality of the mechanism were r4, β, r1 and r5, which contributed 67.77% of the total product variation. It followed therefore that in order to improve the quality of the mechanism the tolerance of these factors must be tightened. Through a series of confirmation experiments, it was revealed that tightening the tolerance resulted in an increase in the multiple performance index (MPI) by 0.094, which was an increase of 19.87% of the initial value.

Multiple response optimization in a fully automated FAB: an integrated tool and vehicle dispatching strategy∗

In today's tight, competitive, and volatile market in semiconductor manufacturing, a successful semiconductor manufacturer has to look into multiple performance indices such as cycle time and on-time delivery. Effective dispatching mechanism is a widely used strategy to achieve these performance indices simultaneously. In the past, dispatching studies in semiconductor manufacturing have primarily focused on the level of tool dispatching. This paper presents an integrated tool and vehicle (ITV) dispatching strategy to consider multiple performance measures in a fully automated fab environment. The ITV dispatching strategy was developed using a state-dependent methodology and multiple response optimization. In order to build a simulation-based automated fab, an integrated modeling approach was proposed to automate both the manufacturing process and the automated material handling system. A case study based on a local fab is described to examine the performance impact of the ITV dispatching rule measured by cycle time, work-in-process, on-time delivery, and lot delivery time. The results of the simulation experiments and analysis show that the ITV dispatching rule is superior to the use of a static dispatching rule, consisting of an average of 15% improvement for on-time delivery and 5% for other performance measures. Furthermore, the proposed modeling framework features high-fidelity, real-time operations and re-configuration; and it can be easily used in other applications.

Numerical Solution for Large-Scale Systems with General Multiple Linear-Quadratic Structure

A class of large-scale linear control systems, where the overall objective function is a nonlinear function of multiple quadratic performance indices, is investigated in this paper. Chebyshev spectral approximation technique is used for state and control variables. Numerical example has been given at the end of this paper.

Optimal state estimation of multicomponent batch distillation

Various methods based on extended Kalman filter, adaptive fading Kalman filter and steady state Kalman filter have been presented for inferential estimation of compositions from temperature measurements in multiple fraction multicomponent batch distillation. This dynamic model based state estimators incorporate component balance equations together with thermodynamic relations, that include bubble point temperature computation and avoid constant relative volatility concept. A performance criterion with multiple performance indices is used to assess the composition estimators. The sensitivity of the estimators is studied with respect to the effect of number of measurements, measurement noise, and filter design parameters including initial state covariance, process and observation noise covariance matrices. The results of the state estimation methods are evaluated by applying them for composition estimation on all trays, reboiler, condenser and products of a ternary hydrocarbon system. The results show the better suitability of the method of extended Kalman filter for composition estimation in multicomponent batch distillation.

Multilevel dynamic programming for general multiple linear-quadratic control in discrete-time systems

This paper extends the reach of dynamic programming to general multiple linear-quadratic control problems in discrete-time systems, where the overall objective is a nonlinear function of multiple quadratic performance indices. A multilevel dynamic programming solution procedure is proposed to obtain an analytical linear control law for this nonseparable control problem. At the lower level the formulated auxiliary Lagrangian problem is of a parametric linear-quadratic structure and is solved by dynamic programming. The weighting vector in the auxiliary Lagrangian problem is adjusted by the upper level iteratively. This two-level process repeats until an optimal condition is satisfied.

Hierarchical control for large-scale systems with general multiple linear-quadratic structure

A class of large-scale linear control systems, where the overall objective function is a nonlinear function of multiple quadratic performance indices, is investigated in this paper. This type of large-scale control problem with a general multiple linear-quadratic structure is nonseparable in the sense of conventional hierarchical control. Hierarchical control is extended in this paper to large-scale nonseparable control problems, where multiobjective optimization is used as a separation strategy. The large-scale general multiple linear-quadratic control problem is embedded, under certain conditions, into a family of the weighted Lagrangian formulation. The weighted Lagrangian formulation is separable with respect to subsystems and can be effectively solved using the interaction prediction approach at the two lower levels in the proposed three-level solution structure. At the third level, the weighting vector for the weighted Lagrangian formulation is adjusted iteratively to search the optimal weighting vector with which the optimal control of the original large-scale nonseparable control problem is attained. One feature of this hierarchical control scheme is a derived analytical solution for the large-scale general multiple linear-quadratic control.

A Four-Level Hierarchical Control Scheme for Large-scale General Multiple Linear-Quadratic Control Problems

Hierarchical control has been extended in Li (1993) to a class of large-scale nonseparable linear control systems, where the overall objective function is a nonlinear function of multiple quadratic performance indices. The solution procedure in Li (1993) applies to the nondegenerate cases. A new hierarchical control scheme with four-level solution structure is proposed in this paper to remove this restriction while deriving an analytical linear control law.

On general multiple linear-quadratic control problems

General multiple linear-quadratic control problems are studied, where the overall objective is a nonlinear function of multiple quadratic performance indices. A multilevel solution procedure is proposed to obtain an analytical linear control law for this nonseparable control problem. The auxiliary Lagrangian problem formulated at the lower level is of a parametric linear-quadratic structure, in which the weighting vector is adjusted by the upper level until a derived optimal condition is met.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Multiobjective optimal generation dispatch based on probability security criteria

An efficient algorithm is proposed to obtain the optimal power flow in power system operation and planning phases by multiobjective optimization. The algorithm makes it possible to treat the optimal dispatch problems with multiple performance indices and to include tradeoff relations between selected indices. The effect of uncertain factors pertaining to power systems can also be taken into account. The effectiveness of the approach is illustrated with numerical examples of the IEEE 30-node, 6-generator system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Matrix criterion robust linear quadratic control problem

This paper studies a robust linear quadratic (LQ) control problem with multiple quadratic performance indices. Specifically, a linear model is assumed to be available for each of a prespecified set of operating points of a system. A vector-valued quadratic control performance index is given at each operating point. It is then desired to find the constant feedback gains of a linear controller to obtain satisfactory control performance over all the operating points. This is a realistic case involving the minimization of a vector criterion of vector criteria, i.e. a matrix-valued criterion. The matrix-valued criterion gives insight into standard robust LQ design, and leads to several related vector minimization problems, and to natural procedures for computing a satisfactory non-inferior solution to the matrix-valued minimization problem.

Combined stress and human performance: a weighted digraph model

Weighted directed graphs are described and offered as possible aids to the analysis of the interactive effects of multiple independent variables on human behavior. Examples in which weighted digraphs represent the interactions among multiple stressors and performance indices are presented, and pulse process analysis is used to derive empirical predictions from the models.