Variable sampling inspection plans with screening for assuring average outgoing surplus quality loss limit indexed by Taguchi’s loss

Taguchi has proposed a variable-quality evaluation called “Taguchi’s quality loss” instead of the attribute quality evaluation such as the proportion of nonconforming items. Arizono et al. have proposed a single acceptance sampling plan based on operating characteristics from the viewpoint of assuring Taguchi’s quality loss. This sampling plan is designed to guarantee the constraints of the prescribed acceptance probabilities for respective lots with the allowable quality loss limit and the unallowable quality loss limit. However, in the acceptance sampling plan based on operating characteristics, the corrective action for rejected lot is not prescribed. On the other hand, the sampling inspection plan with screening is well known as the sampling scheme with the corrective action for rejected lots. Then, there is the attribute sampling inspection scheme with screening in order to guarantee the expectation of the proportion of nonconforming items in the shipping lot. However, the variable sampling inspection scheme with screening has not yet been prescribed. Then, in this article, we propose a variable sampling scheme with screening procedure for the purpose of assuring the upper limit of the maximum expected surplus loss indexed by Taguchi’s loss.     

Variable sampling plan for resubmitted lots based on process capability index and Bayesian approach

Acceptance sampling plans are applied for quality inspection of products. Among the design approaches of sampling plan, the most important one is to use process capability indices in order to improve the quality of manufacturing processes and the quality inspection of products. But, selection of estimators of process capability index and their sampling distribution is very important. Bayesian statistical technique can be used to obtain the sampling distribution. In this paper, a variable sampling plan is developed for resubmitted lots based on process capability index and Bayesian approach. In the proposed sampling plan, lots are inspected several times depending on the quality level of the process. In addition, this paper presents an optimization model for determining the decision parameters of developed sampling plan with regards to the constraints related to the risk of consumer and producer. Two comparison studied have been done including: First, the methods of double sapling plan (DSP), multiple dependent state (MDS) sampling plan, and repetitive group sampling (RGS) plan are elaborated, and also in order to comparing developed sampling plans, an expected number of products as average sample number (ASN) is used for different developed plans; second, a comparison study between Bayesian approach and exact probability distribution is carried out and their results are analyzed. It is observed that the ASN values of MDS sampling plan is less than ASN values of other methods, and also the ASN values of different variable sampling plans based on Bayesian approach is less than ASN values obtained using exact approach.     

Repetitive acceptance sampling plans for burr type XII percentiles

Under truncated life tests, two types of repetitive acceptance sampling plans are proposed to ensure the quality of products in terms of percentile lifetime when the lifetime follows the Burr type XII distribution. The proposed acceptance sampling plans, including the ordinary repetitive acceptance sampling plan and the repetitive version of a group acceptance sampling plan, are developed to meet producer’s and consumer’s risks at two specified lifetime percentiles, simultaneously. Useful tables have been established for a wide range of Burr type XII distributions which include the log–logistic distribution for practical utilization. Finally, some examples are provided for illustration.     

An inspection advisor for form error in cylindrical features

Due to inherent variability in even the so-called “high-precision” machines, the need for accurate, quick and economical inspection of tolerances of machined features has become very important. Coordinate measuring machines (CMMs) are very popular in industry for inspection of components. In addition to hardware capabilities, some of the critical factors that affect the accuracy and precision of inspection using CMMs have been identified as sample size, sampling technique and form evaluation method. Selecting an optimal inspection plan for the CMM is vital to improve the quality of measurements while simultaneously minimizing inspection costs and time. The motivation behind this paper is to provide the user flexibility and control in choosing an optimal inspection plan for evaluation of form error in cylindrical features according to his/her specific needs in a practical manufacturing scenario. In view of this objective, a two-way relationship between the inspection strategy used and inspection performance metrics achieved has been established using multiple regression. The forward model is a plan evaluator that computes numerical estimates of the expected accuracy and precision for different inspection plans. The reverse model is a strategy designer that recommends the most economical inspection plan that can meet the acceptable quality criteria considering the user’s constraints and available resources. Both the models have been incorporated into a user-friendly inspection advisor with a graphical interface.     

A design advisor for the optimal inspection of circularity tolerance

In the wake of growing importance for quality and the need to reduce inspection costs simultaneously, the need for a scientific method of selecting an optimum inspection strategy for coordinate measuring machine (CMM) based inspection has become very important. The inspection error resulting from CMM inspection is greatly affected by the profile irregularities and the sampling strategy, which includes sample size, sampling methods, and algorithms used for form evaluation. This paper describes a system that can recommend an optimal inspection plan based on the needs of the user. A design of experiments (DOE) based approach is used to relate the inspection error with sampling strategies. Surface irregularities are included in the form of lobes formed on the profile. A new two-way model is proposed that works in both directions between the sampling strategy and the performance metrics. The results indicate that the number of lobes and the sampling method used have little impact on the inspection error, while the sample size and form evaluation algorithms have a significant influence. An inspection plan advisor is presented, which provides an inspection plan based on the estimated shape and acceptable measurement error.     

Simplified resubmitted lot inspection from defect counts

Nowadays, as low defect rates per item are often expected in practice, conventional single sampling for lot acceptance purposes is rendered inefficient or unduly expensive. For specific producer’s and consumer’s quality and risk requirements, resubmitted lot sampling usually needs, on the average, less inspection effort than single sampling to properly discriminate between satisfactory and unsatisfactory batches. An integer nonlinear programming problem is stated in order to determine the optimal resubmitted lot sampling plan based on defect count data with limited producer and consumer risks. Nonaccepted lots may be resubmitted for sampling inspection a certain number of times. The number of nonconformities per sampled unit is assumed to follow a Poisson distribution. Quasi-optimal inspection schemes for screening submitted lots of manufactured material are derived in closed-forms by using a normal approximation of the incomplete gamma ratio function. Explicit and quite accurate approximations of the smallest number of units to be tested per lot and the maximum tolerable number of nonconformities in the selected sample are presented. The number of resubmissions with minimal inspection effort and controlled risks is also computed. An application to the manufacturing of glass is provided for illustrative purposes.     

<Emphasis Type="Italic">Joint Design of Continuous Sampling Plans and Specification Limits</Emphasis>

This paper explores the problem of integrating a Type I continuous sampling plan (CSP-1 plan) and the design of specification limits based on Taguchi’s quality loss function. By adopting the minimax-regret principle, we can obtain the economic specification limits and the optimal inspection policy. This study is an extension of Kapur and Wang’s work. ID="A1"Correspondance and offprint requests to: C.-H. Chen, Department of Industrial Management, Southern Taiwan University of Technology, 1 Nan-Tai Street, Yung-Kang City, Tainan 710, Taiwan, Republic of China. E-mail: chench@mail.stut.edu.tw     

Designing small samples for form error estimation with coordinate measuring machines

We propose a method for designing inspection plans of small size for use in form error evaluation of parts from batch or mass production using coordinate measuring machines. The method exploits a priori information coming from large sample inspection of one or a few parts of the lot. It is based on a regression model fitted to the large sample. The model is used twice. First, it provides the dominant pattern of the surface. Then, the deviations from the model that are relevant to form error are captured by weighting the points of the convex-hull of the large sample with the regression residuals. Based on two case studies, we show that the method provides a good accuracy in the estimation of straightness and flatness with very few measurement points. Comparative results also indicate that the method outperforms both the typical sampling schemes used in industry (random sampling, latin hypercube sampling), which do not exploit a priori information, and a recently proposed method using the same kind of a priori information.     

Automated dimensional inspection planning using the combination of laser scanner and tactile probe

Combining multiple sensors on CMMs (Coordinate Measuring Machines) is useful to fulfil the increasing requirements on both complexity and accuracy in dimensional metrology. Yet, the methodology to plan measurement strategies for systems combining different types of sensors is still a major challenge. Such planning is commonly done in an interactive way. This paper presents a methodology which can create inspection plans automatically for CMM inspection combining a touch trigger probe and a laser scanner. The inspection features are specified based on the extracted geometry features and the associated PMI (Product and Manufacturing Information) items from a CAD model. A knowledge based sensor selection method is applied to choose the suited sensor for each inspection feature. For touch trigger measurements, the sampling strategy considers the measurement uncertainty calculated by simulation. A geometry-guide method is developed for collision-free probing path generation. For laser scan measurements, the required view angles and positions of the laser scanner are determined iteratively, based on which the scan path is generated automatically. The proposed methodology is tested for several cases and validated by measurement experiments. The methodology provides suited planning results and can be used for automated dimensional inspection, i.e. Computer Aided Quality Control (CAQC).     

铜阳极板准备机组中分离装置的设计

目前铜电解生产正向着长周期、高电流密度、高品质的方向发展,拥有完备的自动化极板作业机组是达到高效率、高质量生产的前提,因此,实现高自动化阳极板准备机组十分重要。然而,在传统的阳极扳准备机组中阳极板分离装置和垂直矫耳装置是分离开的,这对提高机组的自动化程度较为不利。本文提供了两套分离装置的设计方案,并对其优缺点作了对比分析。     

复杂系统小子样可靠性综合检验方法

一次计数抽样检验方法是一种基于经典统计理论的试验分析方法,由于它具有较强的通用性,被广泛应用于工程实践中.但该方法由于忽略其他信息的作用,需要较大的试验样本量,不适用于小子样产品的检验问题.为解决上述问题,考虑到子系统的性能在一定程度上能决定全系统的性能,提出适用于串联系统的一次计数抽样综合检验方法.该方法充分利用子系统试验数据,可将子系统试验与全系统试验进行折合,从根本上减少系统的样本量.通过实例仿真分析结果表明,所提出的综合检验方法是合理可行的,较传统计数抽样检验方法所需样本量大大减少,从而满足小子样抽样的要求.     

Inspection allocation planning with two types of workstation: WVD and WAD

Allocating inspection stations is a very important issue for controlling quality and saving cost. The study considers inspection allocation problems for serial production systems with two types of workstations, workstation of attribute data and workstation of variable data, which better represents real practice. In addition, this study considers three possibilities for the treatment of detected nonconforming units, namely, repair, rework and scrap. With the above considerations, a profit model is developed for optimally allocating inspection stations. Moreover, a heuristic solution method is developed and it is proved to have much less computation time, compared with an optimization method based on complete enumeration, especially as the number of workstations increases. The model is highly extensible and applicable. Therefore, it can serve as a production planning guideline to solve the inspection allocation problem for serial production systems .     

A Markovian approach to determining optimum process means with inspection sampling plan in serial production systems

This paper develops Markovian-based models for determining the optimum process means with the consideration of an acceptance sampling plan in a serial production system. This paper studies a production system where products are produced continuously with specified lower and upper specification limits for each stage in the production system for quality assurance purposes. Considering the inherent variability in production processes, the quality characteristic(s) of a product might fall below the lower specification limit, resulting in scrap cost, or above the upper specification limit, resulting in rework costs. To study the dynamics of this problem, this paper first develops a Markovian-based model for the optimum process target level for a single quality characteristic assuming a single sampling inspection plan for both a single- and a two-stage production system. Then, the proposed model is extended for dual quality characteristics that are dependent for single- and two-stage production systems. Numerical examples and sensitivity analysis are performed to investigate the effect of different system parameters on the expected profit and optimum process means. The results showed that both single- and two-stage production systems have convex function for the expected profit. In addition, the results showed that the optimum process means are slightly larger than the average of the specification limits. Finally, the correlation between the quality characteristics affects the expected profit significantly.     

基于质量成本模型的工序检验策略优化研究

控制与优化质量成本将作为制定工序检验计划的一个新的参考点。采用动态规划的方法建立相应的质量成本模型。通过对模型的求解,得到工序检验方式的最优化序列,并进一步分析模型中相关参数对决策序列的影响。     

链条耐磨可靠性指标检验的抽样方法

本文应用最佳检验理论，探讨了链条产品耐磨可靠性指标检验的最佳抽样方法，并给出了各种规格滚子链耐磨可靠性指标检验的抽样方案。     

GA-based synthesis approach for machining scheme selection and operation sequencing optimization for prismatic parts

To obtain global and near-global optimal process plans based on the combinations of different machining schemes selected from each feature, a genetic algorithm-based synthesis approach for machining scheme selection and operation sequencing optimization is proposed. The memberships derived from the fuzzy logic neural network (FL-NN), which contains the membership function of each machining operation to batch size, are presented to determine the priorities of alternative machining operations for each feature. After all alternative machining schemes for each feature are generated, their memberships are obtained by calculation. The proposed approach contains the outer iteration and nested genetic algorithm (GA). In an outer iteration, one machining scheme for each feature is selected by using the roulette wheel approach or highest membership approach in terms of its membership first, and then the corresponding operation precedence constraints are generated automatically. These constraints, which can be modified freely in different outer iterations, are then used in a constraints adjustment algorithm to ensure the feasibility of process plan candidates generated in GA. After that, GA obtains an optimal process plan candidate. At last, the global and near-global optimal process plans are obtained by comparing the optimal process plan candidates in the whole outer iteration. The proposed approach is experimentally validated through a case study.     

Quick decision-making support for inspection allocation planning with rapidly changing customer requirements

Manufacturing products with multiple quality characteristics is always one of the main concerns for an advanced manufacturing system. To assure product quality, finite automatic inspection systems should be available and employed. Inspection planning to allocate inspection stations should then be performed to manage limited inspection resources. Since product variety in batch production or job shop production is increased to satisfy the changing requirements of various customers, the specified tolerance of each quality characteristic varies from time to time. Except for a finite inspection resource constraint, therefore, manufacturing capability, inspection capability, and tolerance specified by customer requirement are considered concurrently in this research. A unit cost model is constructed to represent the overall performance of an advanced manufacturing system. Both the internal and external costs of a multiple quality characteristic product are considered. The inspection allocation problem can then be solved to reflect customer requirements. Since determining the optimal inspection allocation plan seems to be impractical as the problem size gets larger, in this research, two decision criteria (i.e., sequence order of workstation and tolerance interval) are employed concurrently to develop a heuristic method. The performance of the heuristic method is measured in comparison with an enumeration method that generates the optimal solution. The result shows that a feasible inspection allocation plan to meet changing customer requirements can be determined efficiently.     

滚动轴承质检方案的策划与优化

文章首先介绍了质量检验在产品质量控制中的重要性,以及正确的质量检验方案在生产实践中的作用和意义。接着介绍了滚动轴承质检方案的制定和优化方法;即如何根据滚动轴承的用途和服役条件来分析它的质量特性,如何根据轴承的质量特性来策划和优化质量检验项目和检验方法,以及如何确定测量精度和选择计量器具,试验设备和仪器。     

Analysis and inverse substructuring computation on dynamic quality of mechanical assembly

Mechanical assembly has its own dynamic quality directly affecting the dynamic quality of whole product and should be considered in quality inspection and estimation of mechanical assembly. Based on functional relations between dynamic characteristics involved in mechanical assembly, the effects of assembling process on dynamic characteristics of substructural components of an assembly system are investigated by substructuring analysis. Assembly-coupling dynamic stiffness is clarified as the dominant factor of the effects and can be used as a quantitative measure of assembly dynamic quality. Two computational schemes using frequency response functions(FRFs) to determine the stiffness are provided and discussed by inverse substructuring analysis, including their applicable conditions and implementation procedure in application. Eigenvalue analysis on matrix-ratios of FRFs before and after assembling is employed and well validates the analytical outcomes and the schemes via both a lumped-parameter model and its analogic experimental counterpart. Applying the two schemes to inspect the dynamic quality provides the message of dynamic performance of the assembly system, and therefore improves conventional quality inspection and estimation of mechanical assembly in completeness.