Influence of residual thermal stresses on fatigue crack growth life of discontinuous reinforcements in metal matrix composites

The fatigue life prediction model based on crack propagation from micro-structural features is derived and presented for planar and randomly oriented Discontinuous Reinforced Metal Matrix Composites (DRMMCs). The model contains the influence of micro-structural properties such as aspect ratio, volume fraction of particle/fibre and constraint between particle and the matrix. The effect of residual thermal stresses generated within the matrix during development of composite is considered. The particle/fibre plays a dominant role in the development of the cyclic plastic zone size ahead of the crack tip; moreover, it enhances the cyclic plastic deformation characteristics of DRMMC. The theoretical model-based evaluations for low cycle fatigue in DRMMCs are within the proximity of the experimental results.     

The assembly line worker assignment and balancing problem with stochastic worker availability

Assembly lines can be employed successfully in sheltered work centres to better include persons with disabilities in the labour market as well as to improve production efficiency. The optimal assignment of a heterogeneous workforce is known as the assembly line worker assignment and balancing problem (ALWABP). These assembly lines are characterised not only by a heterogeneous workforce, but also by high levels of absenteeism, which makes it more difficult to obtain stable and efficient line balancing solutions. In this paper, an extension of the ALWABP to minimise the expected cycle time under uncertain worker availability is proposed. We model this problem as a two-stage mixed integer program, and propose local search heuristics for solving it. Computational experiments show that stochastic modelling can help to improve the line’s efficiency and that the proposed heuristics produce good results for instances of practical size.     

Level‐set topology optimization with many linear buckling constraints using an efficient and robust eigensolver

Linear buckling constraints are important in structural topology optimization for obtaining designs that can support the required loads without failure. During the optimization process, the critical buckling eigenmode can change; this poses a challenge to gradient‐based optimization and can require the computation of a large number of linear buckling eigenmodes. This is potentially both computationally difficult to achieve and prohibitively expensive. In this paper, we motivate the need for a large number of linear buckling modes and show how several features of the block Jacobi conjugate gradient (BJCG) eigenvalue method, including optimal shift estimates, the reuse of eigenvectors, adaptive eigenvector tolerances and multiple shifts, can be used to efficiently and robustly compute a large number of buckling eigenmodes. This paper also introduces linear buckling constraints for level‐set topology optimization. In our approach, the velocity function is defined as a weighted sum of the shape sensitivities for the objective and constraint functions. The weights are found by solving an optimization sub‐problem to reduce the mass while maintaining feasibility of the buckling constraints. The effectiveness of this approach in combination with the BJCG method is demonstrated using a 3D optimization problem. Copyright © 2016 John Wiley & Sons, Ltd.     

Velocity‐based formulations for standard and quasi‐incompressible hypoelastic‐plastic solids

We present three velocity‐based updated Lagrangian formulations for standard and quasi‐incompressible hypoelastic‐plastic solids. Three low‐order finite elements are derived and tested for non‐linear solid mechanics problems. The so‐called V‐element is based on a standard velocity approach, while a mixed velocity–pressure formulation is used for the VP and the VPS elements. The two‐field problem is solved via a two‐step Gauss–Seidel partitioned iterative scheme. First, the momentum equations are solved in terms of velocity increments, as for the V‐element. Then, the constitutive relation for the pressure is solved using the updated velocities obtained at the previous step. For the VPS‐element, the formulation is stabilized using the finite calculus method in order to solve problems involving quasi‐incompressible materials. All the solid elements are validated by solving two‐dimensional and three‐dimensional benchmark problems in statics as in dynamics. Copyright © 2016 John Wiley & Sons, Ltd.     

Improved robust exponential stability for Takagi–Sugeno fuzzy uncertain systems with time-varying delays

This paper concerns managing the robust exponential stability problem of uncertain Takagi–Sugeno fuzzy systems with time-varying delay by employing a further improved integral inequality matrix approach. Based on the linear matrix inequality (LMI) approach, delay-dependent robust exponential stability criteria have been developed. By taking the relationship among the time-varying delay, its upper bound and their difference into account, some less conservative LMI-based delay-dependent robust exponential stability criteria are obtained without ignoring any useful terms in the derivative of Lyapunov–Krasovskii functionals. Maximum allowable upper bound for time-varying delays is determined. Numerical examples are provided to show that the obtained results significantly improve the allowed upper bounds of delay size over some methods existing in the literature.     

Bond line thickness and die tilt inspection in die bonding process

This study focuses upon building an automated inspection system for the in-line measurement of bond-line thickness (BLT) and die tilt in die attachments in the semiconductor packaging process. A prototype of a visual system utilizing the line scan stereo vision technique via two linear CCD cameras has been developed for the die bonding quality inspection. A novel algorithm is proposed for the determination of the 3D coordinates of certain points on an object. The BLT and die tilt of a die attached chip of substrate height 800 μm and cross section 15 × 15 mm² were measured to be approximately 76.8 μm and 0.00094, respectively. The measurement can be completed within one second. Thus the in-line inspection of die bonding quality can be conducted efficiently using the proposed technique.     

Prediction of color changes in acetaminophen solution using the time–temperature superposition principle

A prediction method for color changes based on the time–temperature superposition principle (TTSP) was developed for acetaminophen solution. Color changes of acetaminophen solution are caused by the degradation of acetaminophen, such as hydrolysis and oxidation. In principle, the TTSP can be applied to only thermal aging. Therefore, the impact of oxidation on the color changes of acetaminophen solution was verified. The results of our experiment suggested that the oxidation products enhanced the color changes in acetaminophen solution. Next, the color changes of acetaminophen solution samples of the same head space volume after accelerated aging at various temperatures were investigated using the Commission Internationale de l’Eclairage (CIE) LAB color space (a*, b*, L* and ΔE*ab), following which the TTSP was adopted to kinetic analysis of the color changes. The apparent activation energies using the time–temperature shift factor of a*, b*, L* and ΔE*ab were calculated as 72.4, 69.2, 72.3 and 70.9 (kJ/mol), respectively, which are similar to the values for acetaminophen hydrolysis reported in the literature. The predicted values of a*, b*, L* and ΔE*ab at 40?°C were obtained by calculation using Arrhenius plots. A comparison between the experimental and predicted values for each color parameter revealed sufficiently high R² values (>0.98), suggesting the high reliability of the prediction. The kinetic analysis using TTSP was successfully applied to predicting the color changes under the controlled oxygen amount at any temperature and for any length of time.     

Change Point Estimation in the Mean of Multivariate Linear Profiles with No Change Type Assumption via Dynamic Linear Model

Change point estimation is a useful concept that helps quality engineers to effectively search for assignable causes and improve quality of the process or product. In this paper, the maximum likelihood approach is developed to estimate change point in the mean of multivariate linear profiles in Phase II. After the change point, parameters are estimated through filtering and smoothing approaches in dynamic linear model. The proposed change point estimator can be applied without any prior knowledge about the change type against existing estimators which assume change type is known in advance. Besides, sporadic change point can be identified as well. Simulation results show the effectiveness of the proposed estimators to estimate step, drift and monotonic, as well as sporadic changes in small to large shifts. In addition, effect of different values of the Multivariate Exponentially Weighted Moving Average (MEWMA) control chart smoothing coefficient on the performance of the proposed estimator is investigated presenting that the smoothing estimator has more uniform performance. Copyright © 2015 John Wiley & Sons, Ltd.     

A Single Sampling Plan Based on Exponentially Weighted Moving Average Model for Linear Profiles

The exponentially weighted moving average (EWMA) model has been successfully used in acceptance sampling plans. The EWMA model provides the quality information of the current lot and the preceding lots. In addition, a multiple dependent state (MDS) sampling plan considers the quality information of the preceding lots. In this study, we present two new sampling plans for linear profiles. One is based on EWMA model with yield index using the single sampling plan, and the other is based on EWMA model with yield index using the MDS sampling plans. The plan parameters are determined by a nonlinear optimization approach. As the smoothing parameter value equals to one, the first proposed plan becomes the traditional single sampling plan. In addition, we compare the proposed plans with the traditional single sampling plan. The results indicate that the MDS sampling plan based on EWMA model with yield index with smaller value of smoothing parameter performs better than the traditional single sampling plan and the single sampling plan based on EWMA model with yield index in terms of the sample size required. One real example is used to illustrate the proposed plan. Copyright © 2015 John Wiley & Sons, Ltd.     

Clustering Empirical Failure Rate Curves for Reliability Prediction Purposes in the Case of Consumer Electronic Products

In this paper, a methodology based on the combination of time series modeling and soft computational methods is presented to model and forecast bathtub‐shaped failure rate data of newly marketed consumer electronics. The time‐dependent functions of historical failure rates are typified by parameters of an analytic model that grabs the most important characteristics of these curves. The proposed approach is also verified by the presentation of an industrial application brought along at an electrical repair service provider company. The prediction capability of the introduced methodology is compared with moving average‐based and exponential smoothing‐based forecasting methods. According to the results of comparison, the presented method can be considered as a viable alternative reliability prediction technique. Copyright © 2015 John Wiley & Sons, Ltd.