Inspection Allocation Planning for a Multiple Quality Characteristic Advanced Manufacturing System

Producing products with multiple quality characteristics is always one of the concerns for an advanced manufacturing system. To assure product quality, finite automatic inspection systems should be used. Inspection planning to allocate inspection stations should then be performed to manage the limited inspection resource. Except for finite inspection station classes, in this work, the limited number of inspection stations, of each inspection station class, is considered for solving the inspection allocation problem in a multiple quality characteristic advanced manufacturing system. Since the product variety in batch production or job shop production increases to satisfy the changing requirements of the various customers, the tolerances specified will vary from time to time. This inspection allocation problem is solved using a unit cost model in which the manufacturing capability, inspection capability, and tolerance specified are concurrently considered for a multiple quality characteristic product. The situation of unbalanced tolerance design is also considered. The inspection allocation problem can then be solved according to customer requirements. Since determining the optimal inspection allocation plan seems to be impractical, as the problem size becomes large, two decision criteria (i.e. sequence order of workstation and tolerance interval) are employed separately to develop two different heuristic solution methods in this work. The performance of each method is measured in comparison with the enumeration method that generates the optimal solution. The result shows that a feasible inspection allocation plan can be determined efficiently. ID="A1"Correspondance and offprint requests to: Dr Yau-Ren Shiau, Department of Industrial Engineering, Feng-Chia University, 100 Wenhwa Road, Seatwen, PO Box 25–097, Taichung 407, Taiwan     

Repeatability/Linearity Study and Measurement Loss Cost Analysis of an Automatic Gauge

Computer-aided inspection (CAI) has become one of the fundamental steps in advanced manufacturing by employing automatic gauges. However, it is necessary to provide a more practical way to evaluate CAI on-line efficiency. Since a gauge capability study should be conducted before applying any automatic gauge, the necessary off-line gauge assesment for CAI is introduced in this paper. An R&R (repeatability/reproducibility) study is commonly conducted in the gauge capability study, but in this paper, an R&L (repeatability/linearity) study of a machine vision system is investigated and introduced. The ANOVA approach and regression approach are applied and compared to study the linearity effect. The measurement loss cost includes extra costs (i.e. costs of discarding, reworking, inspection, and quality loss) that arise from measurement error. These costs are analysed by interpreting the relationships between manufacturing capability, gauge capability, and the tolerance. As most gauge capability studies were conducted for the bilateral tolerance inspection, unbalanced tolerance inspection is considered here. The way that the relative costs contribute to the measurement loss cost is also studied. Rather than using a constant measurement error determined by previous observations, the measurement error model is embedded in the relative cost models. Users can then evaluate CAI on-line efficiency by incorporating the measurement error when the tolerances are rapidly changed to satisfy customer requirements.     

On-machine measurement using a noncontact sensor based on a CAD model

Once a machining process is finished, an inspection process is carried out to check whether the part is within dimensional tolerances. A coordinate measuring machine (CMM) is a general metrological device for assessment of dimensions on the shop floor. It cannot be ignored, however, that CMM measurements require significant resources in operating time and cost, which has led to many studies into on-machine measurement (OMM) systems. This study aims to develop an OMM system with a noncontacting laser displacement sensing apparatus and a computer-aided design (CAD) model for ease of operation, improved operating speed, and free form profiling. The system is composed of two software modules, one for sensor alignment with the machine tool and the other for measurement based on CAD/CAM (computer-aided machining). Consequently, the system was verified on the shop floor at a numerical control (NC) machining center.     

Conformance and nonconformance in segmentation-free X-ray computed tomography geometric inspection

Additive Manufacturing (AM) is changing the manufacturing paradigm as it makes it possible to generate complex geometries that are impossible using conventional technologies. However, conventional GPS/GD&T practices are inadequate both at specifying and verifying geometric tolerances. In both cases, they lack the required flexibility. Applying volumetric instead of surface representations helps to solve the problem of specifying tolerances and coheres with topological optimization. The verification paradigm must be modified, too, as AM allows an increase in part complexity without a corresponding increase of cost. Among measurement techniques, only X-ray computed tomography (XCT), which is volumetric, is capable of easily measure complex parts. Leaving the discussion of volumetric tolerance specifications to the future, the aim of this work is exploring a part geometric accuracy verification by direct comparison between its nominal geometry and geometric tolerance volumetric representation, and an XCT volumetric image of it. Unlike the conventional use of XCT for geometric verification, this is a segmentation-free verification. The method is based on the “mutual information” of the two, i.e. information shared by the measured and nominal representations. The output is a conformance statement that does rely on a measurement but nor on a specific measured value not rely on a measurement result. This makes defining a decision rule considering consumer's and producer's risks difficult: uncertainty does not exist in this case. Statistic and simulation techniques make it possible to estimate these risks, defining a numerical model of the distribution of the gray values in a specific portion of the XCT image. Finally, an additive manufacturing case study validates the methodology.     

全跳动综合检查仪的设计与误差分析

针对机械制造质量控制系统中高精度公差检测装置相对缺乏的现状,设计了一台适用于轴类零件的全跳动公差智能综合检测设备,以实现直线度、圆度、端面圆跳动、径向圆跳动、端面全跳动、轴向全跳动等公差项目的自动化测量。详细介绍了全跳动综合检查仪的工作原理、机械结构、硬件电路、软件设计原理,采用低通数字滤波的方法实现实时采样数据处理,有效地抑制了干扰信号,对提高测量精度和测量效率具有实际工程意义;最后分析了机械装置的各项误差对公差测量的影响。     

IN-PROCESS AND POST-PROCESS QUANTIFICATION OF MACHINING ACCURACY IN CIRCULAR CNC MILLING

ABSTRACT

In-process part inspection using a spindle touch probe has gained a significant importance, mainly because parts can remain on the machine without disrupting the machine setup while inspection is being conducted. This practice leads to a shorter inspection time, improved part accuracies, and reduction of scraps. Recently, intense domestic and international competition has put more importance on part quality in terms of producing parts right the first time and maintaining the consistent quality standards. A literature review revealed that a comparative analysis between in-process gauging using a touch probe and post-process inspection using a coordinate measuring machine (CMM) to ascertain part quality has not been adequately studied. Therefore, there is a need for a study to measure the characteristics of the two inspection techniques. To address the problem, cutting experiments were conducted and measurement data were analyzed using a state-of-the-art CNC machine, a CMM, a touch probe, and a high-precision ballbar system. The experimental data show that machined features and touch probe measurements are affected by the inherent shortcomings in machine tool structure, suggesting a machine tool capability analysis be undertaken in tune with the required tolerance specifications prior to machining operations, rather than solely relying on the touch probe inspection for part quality assessment.     

Prediction and analysis of size tolerances achievable in peripheral end milling

Size tolerance is the most critical parameter requiring attention for ensuring dimensional repeatability of manufactured component parts, yet very little research has been reported on this important topic. This paper presents a method for predicting size tolerances of component parts machined through peripheral end milling. The method makes use of prototype software based on previously reported cutting-force and surface-generation models in which the end mill is modelled as a cantilever beam rigidly gripped by the tool holder. It also takes into account the effect of size variation for the cutting tool. The method is validated through several cutting experiments. For further analysis, the method is employed for predicting the size tolerances of a prismatic component by varying one controllable variable at a time and then monitoring the relationship between size tolerance and the variable. When a distinct relationship is noted it is verified both analytically and experimentally. The results indicated that whilst the average size variation, which contributed to the variation of the basic size of component parts, is always proportional to the metal removal rate, the range of size variations that contributed to the size tolerance is not. Therefore, there is scope for increasing the metal removal rate without sacrificing the size tolerance. The knowledge acquired through this research can be applied for selecting an optimum cutting condition using the developed method when the size tolerances of component parts are specified.     

Tolerance-based localization algorithm: form tolerance verification application

Current localization techniques have been successfully used for aligning sculptured surfaces with CAD models in inspection applications. However, tolerance specifications are not considered as an integral part of the localization process. The tolerance verification and comparison with measured surfaces occur at a later step to accept or reject the manufactured part. This two-step process prolongs the inspection time. For the first time, this paper presents a novel localization algorithm for inspection that integrates the tolerance specifications as an optimality criterion. A closed-form solution algorithm that applies 3D rigid body transformation using quaternion and uses a minimum acceptable deviation zone approach was developed. The formulation is based on the mathematical definitions from ANSI Y14.5.1 standards (American National Standard Institute) for form tolerances. The new iterative minimum acceptable deviation zone localization algorithm is formulated using four types of form tolerances: straightness of a median line, straightness of a surface line, flatness and cylindricity. It is applied and compared to several benchmark examples for validation. The results demonstrated the ability of the new localization approach to achieve comparable results but with less computation effort due to using a constraint satisfaction problem and a closed-form solution algorithm in the formulation. The merit of the new approach stems from its ability to increase the efficiency of tolerance verification during the inspection process. The applicability of the proposed algorithm to various types of tolerance is highlighted.     

Optimal tolerance design of assembly for minimum quality loss and manufacturing cost using metaheuristic algorithms

Tolerance allocation is a design tool for reducing overall cost of manufacturing while meeting target levels for quality. An important consideration in product design is the assignment of design and manufacturing tolerances to individual component dimensions so that the product can be produced economically and functions properly. The allocation of tolerances among the components of a mechanical assembly can significantly affect the resulting manufacturing costs. In this work, the tolerance allocation problem is formulated as a non-linear integer model by considering both the manufacturing cost of each component by alternate processes and the quality loss of assemblies so as to minimise the manufacturing cost. Metaheuristics techniques such as genetic algorithm and particle swarm optimisation are used to solve the model and obtain the global optimal solution for tolerance design. An example for illustrating the optimisation model and the solution procedure is provided. Results are compared with conventional technique and the performances are analysed.