Optimum speed of visual inspection using a systematic search strategy

In an earlier paper, the authors presented models of human functioning in visual inspection and derived optimal working speeds to balance the cost of time and the cost of errors. Both self-paced and externally paced models assumed a random search strategy. It was noted that choosing a standard speed for visual inspection is difficult with standard work measurement techniques and that the data required for the suggested search model are easily measurable. The purpose of this paper is to complement the earlier work by deriving similar models employing a systematic search strategy. The two models can be considered as bounds on actual performance; thus the current paper complements the previous one by establishing an upper bound rather than a lower bound on performance in search tasks. Comparisons between the two strategies are presented.     

An integrated cutting speed dispatch policy model

In this paper an integrated model is given for determining the total cost involved in the (1) machining, (2) stock holding, and (3) dispatching of a customer's order for a specified number of machined items. A search procedure has been presented for determining the optimum cutting speed and the optimum number of lots in which the machined items should be dispatched. An example has been solved to illustrate the search procedure.     

Effect of rework,rejects and inspection on lot size with work-in-process inventory

The economic order quantity and economic production quantity models are the most commonly used inventory models in production environments for the calculation of optimum lot size. However, these models are based on the unrealistic assumption that every process produces good quality products every time. Moreover, the impact of inspection is neglected in all extended inventory control models involving work in process inventory. By taking both imperfect production and lot size inspection into consideration, this paper presents a more realistic approach for the modelling of optimum lot size and total cost with a focus on the work in process inventory. A mathematical model is derived for optimum lot size based on the minimisation of the average cost. Our approach incorporates the effect of rework, rejects and inspection on work in process inventory. The significant effect of imperfect production and inspection on optimum lot size is evaluated via numerical examples. In comparison to existing models, the proposed model is a more generalised and flexible form of inventory model for independent demands.     

Inspection and monitoring planning for RC structures based on minimization of expected damage detection delay

The deterioration mechanism of reinforced concrete (RC) structures under corrosion is highly dependent on environment and material properties. Uncertainties in structural damage occurrence and propagation due to corrosion should be considered in a rational way using a probabilistic approach. In this study, such an approach is proposed to establish a life-cycle optimum inspection plan under uncertainty. This plan leads to cost-effective maintenance interventions, considering uncertainties associated with damage occurrence/propagation and inspection methods. Uncertainties associated with prediction of damage occurrence time are considered by using the Monte Carlo simulation. A damage detectability function is used to assess the quality of inspection method according to damage intensity. The inspection planning is formulated as an optimization problem with the objective of minimizing the expected damage detection delay. This formulation is further used for optimum monitoring planning. Effects of number of inspections and/or monitoring actions, quality of inspection, monitoring duration, and uncertainties associated with damage occurrence/propagation are investigated. The proposed approach is applied to an existing highway bridge. This approach can be used to develop cost-effective management strategies by considering effects of damage detection delay on life-cycle cost and performance of deteriorating structures.     

Extending economic design of p charts to handle user specified constraints using a genetic algorithm

For certain processes, the quality of the output can be monitored using attribute inspection statistical process control. Various approaches have been used to determine optimal or near-optimal parameters for such a plan. Since most of these approaches use an unconstrained model, some solutions can result in theoretical and pragmatic problems. In this paper we used Duncan's loss function as the objective function for the development of a Genetic Algorithm (GA). In addition to formulating a GA to find a solution to the model, user constraints concerning the frequency of inspection, the number of defects allowed and the production rate are used to limit the search space for the GA. The GA is selected over other search techniques such as traditional calculus-based, enumeration, or undirected random search methods because the GA is more robust than other search techniques.     

A steepest gradient method for optimum structural design

This paper describes a search procedure for finding the unconstrained maximum or minimum of a function of many independent variables. If this function represents the volume, cost, stiffness, etc. of a structure and each of the independent variables is associated with a parameter governing the geometry of the structure then designs of optimum geometry may be made in certain cases with the assistance of this search procedure. The procedure consists of steepest gradient calculations used in conjunction with a reverse Fibonacci location process. A ridge-following technique is included to speed convergence in addition to localized exploration in the region of an optimum. The search procedure has been programmed for computer use and an outline of its structural design applications is presented together with an example of its efficiency in a specific case.     

A Method for Sequencing Inspection Activities Subject to Errors

A method is presented for determining an optimum sequencing inspection plan for a group of inspectors operating at different skill and cost levels. Production and inspection costs for both accepted and rejected items are considered, and dependencies among successive inspections are permitted. A branch-and-bound technique is used to determine the optimum plan. Results are demonstrated by a numerical example.     

A generalized economic model for joint determination of production run,inspection schedule and control chart design

This paper presents a generalized model for a continuous production process for simultaneous determination of production quantity, inspection schedule and control chart design, with a non-zero inspection time for false alarms. Traditionally, the quality control problem and the inventory control problem have been viewed as two separate problems. Rahim (1994) developed an economic model for joint determination of production quantity, inspection schedule, and control chart design for a typical production process which is subject to a non-Markovian random shock. The model consists of the following cost components: (1) the production setup cost, (2) the inventory holding cost, and (3) the cost of maintaining the quality of the product under the surveillance of an x-chart. The optimal production quanity, the optimal inspection schedules, and the economic design parameters of the control charts were determined by striking a balance among these costs. For mathematical simplicity, it was assumed that production ceases only if the process was found to be out-of-control. However, in reality, this assumption may be inapplicable in many industrial situations. In many production processes the machine must be shut down when a search for the assignable cause is being carried out, even though occasionally the alarm turns out to be false. The purpose of this paper is to generalize the above model to cases where production ceases not only for a true alarm but also for a fixed amount of time whenever there is a false alarm. Examples of Weibull shock models are used to illustrate the proposed generalized model.     

Maintenance scheduling of a manufacturing system subject to deterioration

This paper presents an integrated model for the joint determination of both optimal inspection strategy and optimal repair policy for a manufacturing system whose resulting output is subject to system state. An appropriate maintenance strategy is essential to optimize revenue from a manufacturing system which is in continuous operation and subject to deterioration. The optimum policy balances the amount of maintenance required to increase availability against the loss of revenue arising from the down time: insufficient maintenance leads to an increase in the number of defective items, low profit and low maintenance cost; excessive maintenance results in a reduction in the proportion of defective items, high profit and high maintenance cost. In this paper, an intensity control model adapted to partial information provides an optimal inspection intensity and repair degree of the system as an optimal control process to yield maximum revenue. The solution is obtained through formulating an equivalent deterministic Hamilton-Jacobi equation. A numerical example is provided to illustrate the behavior of the optimal control process. The optimal control process determines a solution to both optimum inspection frequency and optimal replacement policy which results in an optimal production run length of the system.     

Structural maintenance planning based on historical data of corroded deck plates of tankers

A probabilistic maintenance and repair analysis of tanker deck plates subjected to general corrosion is presented. The decisions about when to perform maintenance and repair on the structure are studied. Different practical scenarios are analyzed and optimum repair times are proposed. The optimum repair age and intervals are defined based on the statistical analysis of operational data using the Weibull model and some assumptions about the inspection and time needed for repair. The total cost is calculated in normalized form.     

基于PSO和LSSVM回归的摄像机标定

针对摄像机非线性显式标定时很难精确地建立其复杂的数学模型,本文提出了基于粒子群优化算法(PSO)和最小二乘支持向量机(LSSVM)回归的摄像机非线性隐式标定方法.该方法采用最小二乘回归机精确逼近图像坐标与世界坐标之间复杂的非线性成像关系;利用PSO算法搜索LSSVM回归模型的最优参数,提高LSSVM回归的收敛速度和泛化能力.通过运用标准BP神经网络、遗传算法、LSSVM及粒子群优化的LSSVM回归方法对圆阵列图案标定模板进行标定,实验结果表明:基于PSO和LSSVM回归的标定方法具有标定精度高、收敛速度快、泛化能力强等优点.     

基于蚁群算法的资源均衡优化决策及其MATLAB实现

资源均衡问题已被证明属于组合优化中的NP-hard问题,随着网络计划的复杂化,传统的数学规划法和启发式算法已很难解决该问题。本文以各种资源标准差的加权之和作为衡量资源均衡的评价指标,建立了资源均衡优化决策的数学模型,其次,自行设计蚁群算法步骤,利用Matlab编程进行实现,将蚂蚁随机分布在可行域中,蚂蚁根据转移概率进行全局搜索或局部搜索,经迭代求解资源平衡的全局最优和对应的各工序的开始工作时间,最后使用单资源均衡和多资源均衡两个算例对算法进行了测试,验证了该算法的有效性。     

Cost-based optimal relation between inspection time and assessment time for random fatigue crack growth

Optimal inspection time for random fatigue crack growth is theoretically investigated based upon cost-minimization, using a diffusive crack growth model. The optimal inspection time is defined so as to minimize the expected total cost expended up to the assessment time, at which the effect of an inspection is quantified. Assuming that (i) only one inspection is done up to the assessment time, and (ii) the component is immediately replaced if a crack is detected by the inspection, we formulate the expected total cost by the use of the diffusive crack growth model, where randomness associated with the material inhomogeneity, the initial crack length and crack-detection is taken into analysis. Through numerical calculations, we derive the optimal inspection time as well as the optimal expected cost. Finally, we perform parameter sensitivity analyses, and discuss the optimal selection of the assessment time.     

The Design of Economic Acceptance Sampling Plans for a Mixture of Variables and Attributes

A method is developed for determining economical acceptance sampling plans where the characteristics of interest are a mixture of variables and attributes. The method uses a model which has been developed to represent the total expected cost per lot of exercising acceptance sampling. An optimum plan is found by minimizing the expected cost model with respect to the decision variables which are the sample sizes and control limits on the sample means for variables and the sample sizes and acceptance numbers for attributes. Optimization is accomplished using the pattern search.     

考虑运输速度和碳排放的易腐食品供应链网络优化研究

针对易腐食品供应链网络的特征,将运输速度、腐败率考虑在内,建立了一个混合整数非线性（MINLP）模型,利用YALMIP软件求解以达到使整个供应链总成本最少和碳排放量尽量少的目的。最后,通过算例分析证明该模型的可行性,得出碳排放量与车速相关及车辆的最佳运输速度,并利用灵敏度分析,揭示碳单位价格和腐败率的变化对整个供应链的影响。     

Optimum condition-based maintenance policies for deteriorating systems with partial information

Systems are considered which deteriorate as time goes on and whose conditions can be observed. The optimum maintenance policy with respect to cost is determined, based on a continuous deterioration process, by formulating the decision process as a discrete Markov decision problem. Examples from the field of civil engineering are given. The relation between the type of deterioration and condition-based optimum inspection intervals, optimum repair level, minimum average maintenance costs and mean time to repair is shown, using some numerical results.     

Considerations of accuracy and uncertainty with kriging surrogate models in single-objective electromagnetic design optimisation

The high computational cost of evaluating objective functions in electromagnetic optimum design problems necessitates the use of cost-effective techniques. The paper discusses the use of one popular technique, surrogate modelling, with emphasis placed on the importance of considering both the accuracy of, and uncertainty in, the surrogate model. After a brief review of how such considerations have been made in the single-objective optimisation of electromagnetic devices, their use with kriging surrogate models is investigated. Traditionally, space-filling experimental designs are used to construct the initial kriging model, with the aim of maximising the accuracy of the initial surrogate model, from which the optimisation search will start. Utility functions, which balance the predictions made by this model with its uncertainty, are often used to select the next point to be evaluated. In this paper, the performances of several different utility functions are examined, with experimental designs that yield initial kriging models of varying degrees of accuracy. It is found that no advantage is necessarily achieved through a search for optima using utility functions on initial kriging models of higher accuracy, and that a reduction in the total number of objective function evaluations can be achieved if the iterative optimisation search is started earlier with utility functions on kriging models of lower accuracy. The implications for electromagnetic optimum design are discussed     

Optimal inspection and preventive maintenance of units with revealed and unrevealed failures

The maintenance of a single unit system that alternates operating and idle periods is studied. In the former case the failures are detected as soon as they occur and only by special testing or inspection in the latter. This paper aims at minimizing the cost per unit of time for an infinite time span by selection of a unique interval, for both inspection and maintenance. A special feature of this model is the possibility of a less than perfect testing as the inspections may fail and give a wrong result. It is further assumed that both preventive and corrective maintenance make the unit as good as new with the durations of inspections and maintenances being negligible. The existence of an optimum interval and how it depends on both the cost parameters and the reliability characteristics of the unit is discussed.     

Economic Multiattribute Acceptance Sampling

A mathematical model for multiattributes acceptance sampling systems is presented. Through this model the expected total cost of quality control per lot can be determined under the assumption that rejected lots are scrapped. The lot proportion defective for each attribute type is treated as an independent random variable. Any appropriate distribution may be used to describe the random nature of proportion defective for a given attribute type. Optimization of the model is achieved through a well known search technique and is illustrated through an example problem. Sensitivity analysis of the optimum to changes in the assumed prior distributions is presented.     

On the Optimality of a Simplified Multicharacteristic Component Inspection Model

Inspection for multicharacteristic components is an important means to assure product quality. A component is inspected with respect to its characteristics of which non-conformance of one would result in the rejection of the component. Based on a cost-minimization model developed recently by Raoul et al., this paper develops a simplified version of the model to capture the cost implication of false rejection, false acceptance and inspection of the components. The simplified model is computationally more efficient than the earlier one. Optimality of the sequencing of characteristics to be inspected is explored. Based on the simplified model, the optimal number of cycles for inspection can be readily determined. A stopping rule is developed for the search of the optimal number of cycles. Sufficient conditions for performing one cycle of inspection or no multicharacteristic inspection at all are given. Finally, the results are extended to the case where the probabilities of defectives are random.