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A correct performance of measurement systems is a key element in the Quality effort of manufacturing organizations. At least as important as calibration processes, Measurement System Analysis is essential to ensure a solid baseline for decision making. Confirming this relevance, Measurement System Analysis is one of the quality core tools for automotive industry, as ensures the validity of the measurements obtained. In variables measurement, some indicators describe different aspects of the measurement system performance, and simultaneously serve as validation criteria for system acceptance. Probably the most important two indicators are the gage repeatability and reproducibility as a percentage of the total process variation (%GRR) and the number of distinct categories (ndc), for which threshold values apply (%GRR should be less than 10% and ndc should be greater than 5). In this paper we enhance the fact that these two indicators aren't independent, and the threshold values are incoherent, creating a possible conflict when deciding the acceptance of a measurement system.

Since every mistake made in the healthcare industry can cause permanent harm or even death, some fundamental requirements should be considered when planning and designing operating rooms. Lighting is one of the most important ergonomic factors, especially for operating rooms. This paper investigates the integration of the lean approach and six sigma in measuring the efficiency of LED technology, which can also be regarded as a factor affecting the operating room efficiency. Measurement System Analysis (MSA) and Gage Control methods were applied to determine measurement variability in operating room illumination measurement process. Repeatability and reproducibility (%R&R) was found 12.89%. After calibration, %R&R value was found 8.21%, which implies that calibration helped reduce variability.

In the current era of globalization, the perceived quality competition globally is manufacturing. Manufacture industry competition makes companies must concentrate on product quality. and the quality of the factors affecting the product is wrong, such as human resources, tools / machines, and the environment can also cause product quality. And one of the companies engaged in the manufacturing industry, namely PT. APT has a problem with the quality measurement of the dimensions of size on one of the products made, where the product can’t be accepted by the customer and declared reject on all the number of products sent. There are indications of QC checking errors within the company so that reject products are accepted as acceptable. The purpose of this research is to find out what are the main causes of goods declared acceptable internally within the company and when it arrives at the customer is declared reject. And find solutions to how such mistakes do not happen again. To solve this problem, this study uses the MSA (Measurement System Analysis Gage R&R) method which has the advantage of knowing the cause of quality problems in detail whether from the people, tools, or supporting factors in a measurement. So that mistakes that occur before do not happen again and the company can run more effectively, efficiently and consistently in measuring and checking.

Assessment of process health is an important aspect of any quality system. While control charts are often used in the day-to-day operations of processes, it is also helpful to take a retrospective ...

Today’s Agriculture vehicles (AgV)s are expected to encompass mainly the three requirements of customers; economy, the use of High technology and reliability. In this manuscript, we investigate the technology solution for efficient health monitoring and diagnostic (HM&D) strategy to maximize the field efficiency and minimize the machine cost. Based on the data captured by various IoT sensors, we demonstrate the facts to shift the HM&D technology from costly sensor to economic microphone based mechanism. The adopted strategy is capable to reduce the bulky data transmission on the internet, and to increase the up-time of AgVs. We experimented on the essential red hot chili peppers system of the AgV’s backbone hydraulic system—the hydraulic filter and pump. The measurement system analysis is adopted to determine the preciseness of data captured near the considered components. The envision of the correlation between the collected data extracts significant information to draw the facts to embrace the future HM&D technology shift. Correlation between the signals captured from costly sensors and Microphone for the generated faults in hydraulic components demonstrates the effectiveness of audio to replace existing HM&D technology.

PurposeThe aim of this paper is to deploy Six Sigma (SS) methodology for addressing the customer complaints pertaining to Chemical-X in an Indian chemical company.Design/methodology/approachThe study followed a structured Define, Measure, Analyze, Improve, Control (DMAIC) approach to address the customer complaints. The complaints have been classified into different categories along with a project charter in the define phase. In the measure phase, measurement system analysis (MSA) and supplier, input, process, output and control (SIPOC) have been applied. In the analyze and improve phase, why–why analysis, process capability study, how–how analysis, Gage repeatability and reproducibility and Taguchi design have been applied to optimize the manufacturing process parameters for Chemical-X. Lastly, in the control phase, validation of 20 batches has been piloted to validate the optimized parameters.FindingsThe findings of this study highlight the optimization and prioritization of the process parameters. It shows that humidity has the least impact on the manufacturing of Chemical-X, whereas shift type has the maximum impact. The experimental output indicates that the 1st Shift, the holding time after grinding should be twenty-four hours, and the temperature after grinding should be 40 °C to reduce the customer complaints concerning lumps formation in Chemical-X.Research limitations/implicationsThe study is performed for a single product (Chemical-X). It has focused only from the manufacturing process view and not from the transportation, suppliers and downstream supply chain view.Originality/valueA systematic and data-driven approach of the SS methodology ensured that the customer complaints due to lumps formation reduced from 5% (approx.) to 1% (approx.) which resulted in the cost saving of INR 4 million (approx.) annually.

For some quality inspection practices, subjective judgements based on the inspectors' experience and knowledge, such as visual inspection, may be required for some particular quality characteristics. This kind of measurement system, including its associated randomness and fuzziness, should be assessed by Measurement system analysis (MSA) before its application. For such purpose, this article represents observations with randomness and fuzziness from MSAs as fuzzy random variables, and then two pairs of descriptive parameters, i.e., expected value and variance, are derived. Then, the relationship of the total sum of squares of factors is proven to hold, so that fuzzy analysis of variance (FANOVA) in terms of gauge repeatability and reproducibility can be developed. The proposed approach has the advantage that FANOVA is developed based on the relationship of the total sum of squares of factors, considering randomness and fuzziness. A real case in the semiconductor packaging industry is used to demonstrate the applicability of the proposed approaches to MSA.

PurposeThe purpose of this study is to analyze door-panel alignment defects seen in built-in ovens manufactured in one household appliances company's plant. Alignment defects in oven door panel substantially affect aesthetics of the product which is an important aspect in driving customer preference and satisfaction. Therefore, this study aimed to increase the initial 3.1 sigma level of oven-manufacturing process to at least 4 sigma level by decreasing a particular door-panel alignment defect, which constituted 67.7 percent of the overall alignment defects.Design/methodology/approachThe goals were achieved through a structured Six Sigma implementation with lean element by utilizing various Six Sigma tools such as workflow, Pareto-analysis, measurement system analyses, control-charts, process capability analysis, cause-and effect-diagram and hypotheses tests. A non–value-added step was also eliminated through the lean approach.FindingsThrough Six Sigma implementation, the initial 3.1 sigma process performance level has been increased to 4.4 sigma level leading to substantial decrease in alignment defects.Originality/valueIn the quality management literature, not many papers directly deal with aesthetics and appearance problems of the products especially in the household appliances industry. Moreover, hypothesis testing is not frequently used in Six Sigma implementations in the literature. In addition to limited usage of hypothesis testing, very few studies conducted a thorough measurement system analysis. Considering these gaps in the Six Sigma literature, this study fills an important gap in research by implementing a detailed Six Sigma study, enhanced with hypothesis testing and a thorough measurement system analysis, on the aesthetics and appearance of the product.

Additive Manufacturing is on the threshold of full industrial use in various leading industries. This is due to the continuous development of machine systems regarding availability, stability, reproducibility and repeatability alongside their ever-increasing productivity. To achieve high quality parts, process variables must be monitored during production, for example with a Melt Pool Monitoring (MPM) system to measure their characteristics. Initial and long-term stable calibration of the monitoring system must be ensured with proper alignment, positioning and the size of the measuring surface itself. To secure direct comparison of multi-optics within a machine as well as transferability from machine to machine, a quantitative intensity calibration must also be carried out. This paper provides a new calibration approach with measuring equipment and tools including a Measurement System Analysis (MSA), exploring possibilities and limitations in terms of absolute accuracy, repeatability and reproducibility as well as workflows for the measurement equipment and machine calibration.

This article investigated measurement system analysis and system thinking in Six Sigma, as well as the factors that influence these actions. If the measurement system being used to accumulate data from the process delivers dependable and accurate results, the measurement system analysis regulates it. Process improvement initiatives can be derailed by faulty measurement systems. Also, managers who have read faulty data can be misled into making wrong decisions. To collect trustworthy data, a reliable measurement system is established with this process. A method to assess an organization as a system and interpret its practices as a whole with Six Sigma is system thinking. Also, fixing a system as a whole helps to identify the real causes of issues and to know where to address them. This article addressed the contribution of these two methods to an overall success of an organization operating Six Sigma. The most current variables, concepts, and models were studied within operations and project management. By using a design-science-investigate strategy, this study approved of a valuable growth reveal for reasonable and hypothetical application. This study allowed us to generate a fitting assessment model that will fill the research void. Also, this study contributed to the engineering field with improved project success rates and team communication.

Background—Visual inspection is an important element of aircraft engine maintenance to assure flight safety. Predominantly performed by human operators, those maintenance activities are prone to human error. While false negatives imply a risk to aviation safety, false positives can lead to increased maintenance cost. The aim of the present study was to evaluate the human performance in visual inspection of aero engine blades, specifically the operators’ consistency, accuracy, and reproducibility, as well as the system reliability. Methods—Photographs of 26 blades were presented to 50 industry practitioners of three skill levels to assess their performance. Each image was shown to each operator twice in random order, leading to N = 2600 observations. The data were statistically analysed using Attribute Agreement Analysis (AAA) and Kappa analysis. Results—The results show that operators were on average 82.5% consistent with their serviceability decision, while achieving an inspection accuracy of 67.7%. The operators’ reproducibility was 15.4%, as was the accuracy of all operators with the ground truth. Subsequently, the false-positive and false-negative rates were analysed separately to the overall inspection accuracy, showing that 20 operators (40%) achieved acceptable performances, thus meeting the required standard. Conclusions—In aviation maintenance the false-negative rate of

Volume resistivity is one of basic material properties determined for electrical insulating materials. In many cases, the measurement process can affect the accuracy of the measured data. Therefore, this paper analyzes the measurement process while measuring this parameter. A necessary step to perform the analysis is the analysis of the variability that may arise in the whole measurement process. A controlled experiment is then designed to investigate the factors assumed to influence the measurement result based on this analysis. This controlled experiment is followed by experiment evaluation, results analysis, and a suggestion of possible process or organizational changes that can be made to the measurement system to improve the monitoring of material properties using this diagnostic method. The tests performed showed an expected result: the shorting book and the electrostatic bracelet affect the measured value of the volume resistivity but every parameter to a different degree.

In our study a robot was used to deliver objects for measurement into the Equator gauging system. To investigate the robot’s manipulation influence on dimensional measurements, the robot’s tasks were divided into basic functions. Based on these basic functions, nine different robot-manipulation scenarios were defined, i.e., from zero to full robot manipulation, for two measuring objects (named Magnet and PKR) and six measurement characteristics (rectangular and spherical). The robot’s manipulation influence was determined on the basis of the statistical parameters Cp, R, and the 6σ obtained from a measurement system analysis (MSA) type-1 study. The results show that the degree of implemented manipulation of the robot affects the scattering of the measurement data. However, the effect is much more pronounced in the case of length measurements than with spherical geometries. Different measuring methods (touch-triggering or scanning measurement mode, number of sampling points) were used, which showed similar measurement data. This directly indicated the influence of the robot’s manipulation on Cp, R and 6σ. Increasing the degree of the robot’s manipulation decreases the Cp value and increases the R and 6σ values for the length measurements. There is no such pronounced course in the spherical geometries, where the values of Cp, R and 6σ remain approximately the same. The main influential factor for decreasing the Cp value with increasing robot manipulation was the angular misalignment of the object’s orientation in the fixture.

The research study aims to evaluate the precision of the measurement system using Gauge R&R. An experimental research design adopting a positivist empirical approach with deductive strategy was followed to assess the effectiveness of Crossed Gauge R&R technique for validating a measurement system using destructive testing. Crossed Gauge R&R technique in Minitab was found to be highly effective in quantifying different components of measurement variation relative to process variation. Clue generation from the Crossed Gauge R&R study combined with manufacturing and measurement process know-how helped in identifying and eliminating the root causes for measurement variation. Overall Crossed Gauge R&R proved successful in validating the burst strength test equipment. However, it should be noted that manufacturing and test equipment played an equally important part in developing and executing the gauge R&R study and accurately analysing the results. So, Crossed Gauge R&R should be used as an aid rather than the solution for measurement system validation.

Measurement system analysis has a pivotal role in assessing the measuring error when conducting empirical studies. Gage Repeatability and Reproducibility (GR&R) studies are classic methods applied to evaluate measurement system adequacy for a particular application. However, previous published studies are limited to determine the source of measuring error related to not only reproducibility but also repeatability. Hence, the objective of this research is to propose new indicators for measurement error detection due to both repeatability and reproducibility variation in GR&R studies. These indicators were calculated using standardized scores from the analysis of variance. The proposed procedure has been applied not only to literature data but also to a stainless steel cladding process on surfaces of carbon steel. While literature method has detected only reproducibility error, the proposed procedure were able to detect both reproducibility and repeatability sources of measuring error.

In today's world of increasing international trade, companies are suggested to learn, implement and maintain new production techniques in place of traditional production systems in order to sustain their assets. In this approach, we have worked on “Six Sigma”, one of the strongest components of these so-called systems. Within the scope of this study, Six Sigma and its application areas are investigated, and as a result of the obtained findings, six sigma applications have been made in the textile industry where the quality is desired to be improved. In the study, conducted by following the six sigma's DMAIC (Define, Measure, Analyse, Improve, Control) steps, using the detection tools such as SIPOC (Suppliers, Inputs, Process, Outputs, Customers) diagrams, measurement systems analysis, root cause analysis, determination of poor quality sources and improvement on the basic problem have been made. The variation of the strips from the card and cer machines in the plant created great quality problems. Before the six sigma project, the average coefficient of variation value of the card machines was 2.02. With this project, the average coefficient of variation value of the card machines is aimed to be reduced to 0.5-1.5 range. After the six sigma project, the average voefficient of variation value of the card machines was reduced to 1.03.

Optical surface measurement (OSM) systems are able to reveal local surface variations in detail compared with stylus-based metrology. The major challenges of conducting measurement system analysis (MSA) for such an OSM include inconsistent measurement locations and a lack of characterization of gage capability at local surface areas (areal MSA). In this paper, an improved surface model is proposed to enable areal measurement system analysis for OSM by fusing surface manufacturing process information with spatially correlated data. Case studies discussed the MSA techniques developed from the proposed surface models and compared their performance in characterizing the areal MSA.

We investigate how to estimate error probabilities for binary measurements and tests when a gold standard is not available. Recent studies have shown that, without a gold standard, the widely used false-acceptance probability (FAP) and false-rejection probability (FRP) are difficult to estimate. We show by mathematical analysis that this problem is inherent to the unavailability of a gold standard. Instead, the proposed method determines the random components of the error probabilities: the inconsistent acceptance and rejection probabilities IAP and IRP. The method is efficient and robust as the number of model parameters is not predetermined but depends on the goodness of fit.

This paper presents an optical distance evaluation solution, for a sun tracker robotic arm, with the help of Six Sigma. With the help of statistical tools any measurement system can be evaluated and a measurement system analysis (MSA) can be easily made. Like every measurement system, optical distance measurement can have errors. Six Sigma tools can evaluate the measurement system and can give useful data about its accuracy. Sometimes measurement system evaluation is done twice. First, initial tests are done, after some fine tuning and error correction is performed, and finally a repeated test is done, to show that the measurement errors were corrected.

Testing samples in a laboratory to study a design and make predictions about a population is a very common practice in engineering. Arguably almost as common is the practice of treating these measurements as gospel, ignoring the possibility that the results extracted, and the conclusions drawn, could change if a margin of error of the measurement was considered. This paper describes a statistical exercise to study and improve a measurement system error through Measurement System Analysis techniques using JMP software. It consists of a two-step procedure that enables publishing measurements along with their precision. The exercise was done on a system that measures thermal resistance of liquid-cooled cold plates. The cold plate designs were for an electronic package of a GPU (Graphics Processing Unit). The measurement system error was quantified, analyzed, and reduced by a factor of 2.2 times its initial value.

The aim of the project is to develop a sine wave generator and a measuring system suitable for testing speakers made in an acoustic factory. The compactness of the device is characterized by the fact that it can be easily calibrated in a few steps and used in the production area or in laboratories with the right instrument frame. The device is based on an RPI 4B single-card computer running self-developed software that makes working with the system enjoyable and easy with a graphical interface. This article presents the necessity and structure of the system itself, a description of its functions, a measurement system analysis (MSA), and finally the results of a distortion measurement.

In most degradation tests, the measuring processes is affected by several conditions that may cause variation in the observed measures. As the measuring process is inherent to the degradation testing, it is important to establish schemes that define a certain level of permissible measurement error such that a robust reliability estimation can be obtained. In this article, an approach to deal with measurement error in degradation processes is proposed, the method focuses on studying the effect of such error in the reliability assessment. This approach considers that the true degradation is a function of the observed degradation and the measurement error. As the true degradation is not directly observed it is proposed to obtain an estimate based on a deconvolution operation, which considers the subtraction of random variables such as the observed degradation and the measurement error. Given that the true degradation is free of measurement error, the first-passage time distribution will be different from the observed degradation. For the establishment of a control mechanism, these two distributions are compared using different indices, which account to describe the differences between the observed and true degradation. By defining critical levels of these indices, the reliability assessment may be obtained under a known level of measurement error. An illustrative example based on a fatigue-crack growth dataset is presented to illustrate the applicability of the proposed scheme, the reliability assessment is developed, and some important insights are provided.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES The low or no reliability of a measurement system (MS) can lead to occurrences that limit or even hinder the provision of services or the development of products. This problem is linked to factors such as inexistence or deficiency of internal procedures, lack of preventive maintenance, calibrations at irregular intervals of time, or failure to perform it, failure to observe interim checks, among others. The present research has the objective of proposing a procedure for interim check of Coordinate Measuring Machine (CMM) with the use of a device. This problem is mainly related to factors such as the difficulty of establishing a technique, the total measurement volume of CMMs, and the manufacture of devices with good thermal stability, easy calibration, and low cost. To achieve the objective, a systematic review is conducted to collect scientific evidence that contributes to identifying which type of device is most suitable for performing CMMs interim checks. After the identification, the operational characteristics of the CMMs used in the study are recognized, wherefrom the data collected and the research carried out, three devices are designed specifically to perform interim checks. One of these devices, the ball ruler, is built and has its usability for interim check verified through Measurement Systems Analysis (MSA) studies. Finally, an interim check procedure is proposed based on the results achieved by the research and on the international standards and norms related to the theme. A baixa ou nenhuma confiabilidade de um sistema de medição (SM) pode acarretar ocorrências que limitam ou até mesmo inviabilizam a prestação de serviços ou o desenvolvimento de produtos. A esse problema, são vinculados fatores como: inexistência ou deficiência de procedimentos internos, falta de manutenções preventivas, realização de calibrações em intervalos de tempo irregulares, ou sua não realização, inobservância de checagens intermediárias, entre outros. A presente pesquisa possui o objetivo de propor um procedimento para checagem intermediária de Máquina de Medir por Coordenadas (MMC) com uso de dispositivo. Esse problema está relacionado principalmente a fatores como a dificuldade de estabelecer uma técnica, o volume total de medição das MMCs e a fabricação de dispositivos com boa estabilidade térmica, fácil calibração e baixo custo. Para atingir o objetivo, uma revisão sistemática de literatura é conduzida a fim de coletar evidências científicas que contribuam para identificar qual tipo de dispositivo é mais adequado para executar checagem intermediária de MMC. Após a identificação, são apresentadas as características operacionais das MMCs utilizadas no estudo, onde a partir dos dados coletados e das pesquisas realizadas, três dispositivos são projetados especificamente para realização de checagem intermediária. Um desses dispositivos, a régua de esferas, foi construído e teve sua usabilidade para checagem intermediária verificada através de estudos de Análise de Sistemas de Medição (ASM). Por fim, um procedimento de checagem intermediária é proposto com base nos resultados alcançados pela pesquisa e nos padrões e normas internacionais relacionados com o tema

Ethylene glycol is a super commodity chemical and it has vital roles in various applications. Its co-production with other chemicals, such as ethylene carbonate and glycerol carbonate, has promised cheaper production cost. Its quantification presents a challenge as its contaminants, such as ethylene carbonate, produce a signal-reducing effect in flame ionized detector. The aim of this study is to evaluate external standard to quantify the composition of glycol mixture. Measurement system analysis was employed on the external standard method. Reliability of the external standard is statistically significant with low p-values, excellent capability indices, and high F-values. The external standard is found to have remarkable precision and trueness as both capability indices are mirroring each other. Furthermore, the capability analysis has a strong correlation with quality measurement. Based on capability indices, the limit of detection is recommended at S/N = 25 and the limit of quantification is recommended at S/N = 100 for a reliable measurement. A high degree of reliability is achieved coherently as almost all uncertainties of coefficients of variations are less than 5%. The established method was validated and successfully applied to glycol mixture at azeotropic distillation pilot plant.

Unconventional technology of wire electrical discharge machining (WEDM) is essential in manufacturing precise parts for the aviation, automotive military or medical industry. Precision of dimensions and shapes of machined parts is preserved because of the ability to machine the material after the final heat treatment. However efficient and precise machining also depends on the ability to manufacture as small radiuses as possible, which can be achieved by minimizing the width of kerf. To minimize the width of kerf “Half central composite response surface design” plan of experiment considering gap voltage, pulse on time, pulse off time, wire feed and discharge current was implemented. Measurement system analysis (MSA) was computed for the width of kerf measuring system and based on its results mathematical model of the average width of kerf was found. Optimal setting of statistically significant machine parameters to minimize the average with of kerf was deducted from this model.

Quality management is an essential factor for enhancing the competitiveness of a company, and it is important to determine the capability of the measurement system in process improvement activities for quality improvement. In general, some observed dispersions in measurement-related activities are inherent in the product being measured, while others are due to the measurement system used. Semiconductor products are processed through a complex process, and quality control is performed through various measurement processes during the production process. Among them, wafer testing, which is the last step in manufacturing, is an important process to judge the quality of semiconductor products. In the wafer test process, an automatic test equipment (ATE) is used to check the electrical features of the created chips on the wafer, and to judge whether good or not products. To test wafers in ATE, it is necessary to connect to the chip electrode, PAD. Probe Card is used at this time. As a replaceable part, it is made and used according to the product and is generally in a parallel structure to test more quickly and efficiently many chips on a wafer. Since the probe card is extremely sensitive and detailed component, deformation such as abrasion occurs as it is used and affects the wafer test result. This paper presents an algorithm that can analyze the measurement system using the test result data of the measured wafer in order to maintain the optimum state of the ATE and Probe Card, the measurement system of the wafer test process. And using this algorithm, we propose the automated measurement process quality management system (AMPQMS) for the wafer test process. The real-time measurement system analysis algorithms are utilized several statistical analysis methods that analyzes the repeatability and reproducibility of the instrument. AMPQMS can properly combine various analysis algorithms for each product. The quality of the measurement system is real time managed using the analyzed results by the analysis algorithms.

Due to strict functional product requirements designers are compelled to create products with very tight tolerances. Therefore, strict requirements are set for production and measurement processes with regard to accuracy. This research is based on the application of the VDI/DGQ 3442 standard for the assessment of accuracy of numerical control machine tools.The standard is supported by the study of repeatability and reproducibility of the measuring instrument with the aim of dividing total variability of results into the measuring instrument variability and production variability. This is a way to avoid the complex procedure for assessing measurement uncertainty of the CMM used in the verification procedure.

Quality is generally associated with adhesion to specifications, absence of defects and minimizing variability. When specifications are unclear or incorrect, manufacturing and verification processes become questionable, and productive metrology can provide the tools and guidance to improve knowledge of manufacturing systems, through SPC and gage R&R studies, and specification endeavors, using GD&T definitions. In a case study, a methodology based on the reduction of uncertainties using the aforementioned methods was proposed, leading to improvements and a better understanding of the measurement systems, as well as suggestions for improving geometrical product specifications.

The accuracy inner geometrical dimension of cylinder liner has a positive effect on increasing engine efficiency, reducing oil consumption and prolonging engine life. In order to realize the on-line measurement of the cylinder liner hole diameter and roundness in the intelligent production line, a laser-based measuring system is proposed. First, two methods for calculating the inner diameter are described according to the mathematic model established by us, and the effect of input parameters on calculating results are analyzed by use of the full-factorial design. Next, the means for compensating measurement errors caused by the distance between the center axis of the workpiece and the center axis of the rotary actuator is proposed and analyzed. Then, the repeatability and reproducibility (R&R) test for the laser-based measuring system is carried out by the guidelines of measurement systems analysis (MSA), and the test results show that the R&R of the laser-based measuring system is acceptable. Finally, the tests of the laser-based measuring versus the manual measuring and the laser-based measuring versus the contact measuring are carried out, and the maximum difference for each test is 10 μm and 7 μm, respectively.

The original equipment manufacturers and their suppliers have great importance in automotive manufacturing industry at all over the world. The industry has led the way by technological advancement, innovation and economic growth throughout the industrial history. The most important quality management standard known for the manufacturers of the automotive industry, which has such a great importance for the world, is the quality management system standard numbered 16949 prepared by IATF (International Automotive Task Force). The latest version of the standard in 2016 was created for the industry with the contribution of original equipment manufacturers, suppliers and interested parties. In this study; some basic quality techniques recommended by IATF 16949: 2016 were applied in one of the leading automotive supplier enterprises in Istanbul, Turkey. Some of these standard techniques like measurement systems analysis and data evaluation studies have been applied mainly on metrological activities and their effects on manufacturing processes have been observed. It has been firstly realized that the quality techniques helped to prevent the errors before they occur thus; it leads to increase the quality and the efficiency of the production. Additionally, the processes were better observed and better controlled. Moreover, the communication with the customers was more effective than before by mutually understanding. Finally, it became possible to identify the problems in measurements clearly by analyzing the measurement systems through scientific methods. The all helped to improve the manufacturing processes performance.

The ASME Y14.5 geometric dimensioning and tolerancing (GD&T) and ISO-GPS (geometrical product specifications) standards define tolerances that can be added to components to achieve the necessary functionality and performance. The zone that each feature must lie within is defined in each tolerance. Measurement processes, including planning, programming, data collection (with contact or without contact), and data processing, check the compliance of the part with these specifications (tolerances). Over the last two decades, many works have been realized by the metrology community to investigate the accuracy, the measuring methods, and, specifically, the measurement errors of fixed and portable coordinate measuring machines (CMMs). A review of the literature showed the progression of CMMs in terms of accuracy and repeatability. However, discrepancies were observed between measurements using different CMMs or operators. This paper proposed a GD&T-based benchmark for the evaluation of the performance of different CMM operators in computer-aided inspection (CAI), considering different criteria related to the dimensional and geometrical features. An artifact was designed using basic geometries (cylinder and plane) and free-form surfaces. The results obtained from the interlaboratory comparison study showed significant performance variability for complex GD&T, such as in the composite profile and localization. This, in turn, emphasized the importance of GD&T training and certification in order to ensure a uniform understanding among different operators, combined with a fully automated inspection code generator for GD&T purposes.

Several sources of variation can affect the performance of a mechanical test. Hence, the measurement system performance should be assessed. The gage repeatability and reproducibility study is a method used to assess and quantify the variation of a mechanical test. Since it seems that this method has not yet found its way into the field of sports engineering, this paper promotes its application by demonstrating a practical example based on a current problem in sports shoe development. In detail, a novel mechanical simulation to determine the forefoot bending stiffness of athletic footwear during plantar flexion movement was developed and its quality assessed. The ANOVA Gage R&R study was performed based on 64 randomized trials of eight footwear samples assessed by two appraisers. The mechanical test was evaluated as acceptable for the desired application and the resolution was quantified to be 0.04 Nm/°.

Semiconductor reliability in applications such as automotive is getting increased attention as design rules shrink to include 1Xnm, semiconductor content per vehicle continues to grow, applications become more critical and reliability requirements tighten. Current automotive requirements stipulate less than one defective part per million (DPPM). Approaches to address reliability include improving design, manufacturing and test. Process control in manufacturing is critical for reliability and includes continuous improvement for reducing process tool defectivity, excursion monitoring of process tools and product lines, golden or best performing tool methods [1], measurement system analysis (MSA) methods and screening. Inline defectivity is known to have an impact on both yield and reliability [2], and defects can impact reliability in one of two ways. Killer defects located in areas that are untested can result in so called Zero- Kilometer failures. In other cases, the same types of defects that cause yield loss can also cause latent reliability failures – the difference being size, location and density. Latent reliability defects become activated after test and can include defect types such as partial bridges, partial opens, and embedded particles. Current reliability engineering relies on outlier detection rules like parametric part average testing (P-PAT) [3], or geographic part average testing (G-PAT), both of which are derived from end-of-line screening data, which is based solely on electrical test data [4]. Inline Part Average Testing (I-PAT™) is enabled by multi-channel high-speed LED scanning inspection technology and offers an opportunity to apply fab data to reliability engineering. Defect inspection results are analyzed with machine learning (ML) to weigh the defectivity and create a die-level defectivity metric allowing the statistical identification of die which are a high reliability risk [5, 6]. Two case studies are described. The first case is a feasibility study based on historical fab defectivity data and includes a sample of ~250,000 die, with eight inline defect inspections per wafer, including four front end of line (FEOL) and four back end of line (BEOL), on a high sensitivity broadband inspection system [7, 8]. Each defect is assigned a weight based on its impact to various “ground truth” indicators. The combined impact of all defects in a given die stacked across all inspections is aggregated into a die-level metric. Plotting the die-level I-PAT metrics for all the die as a Pareto chart allows outliers to be identified using accepted statistical methods [9]. I-PAT metrics can then be correlated to electrical wafer sort (EWS) yield or fallout rate, specific wafer-sort bins, EWS parametric test performance and post burn-in electrical test. Of key importance is that wafer test was not used to train the I-PAT model, and therefore this method is an independent validation of latent reliability. The second case study focuses on production screening feasibility with multi-channel high-speed LED scanning, and addresses overkill, or the over inking of potentially good die based on inline defectivity, which is a critical challenge that must be overcome for production implementation [10]. Using inspection enabled by high speed LED scanning technology, die screening is a critical component of a comprehensive automotive Zero Defect program. Applications include early detection of fab excursions, feedback for continuous improvement of inline defectivity, feedforward to optimize electrical test methods and screening of die containing possible latent reliability defects. The I-PAT methodology can be used to enhance standard end-of-line outlier detection rules such as P-PAT [3], which is based solely on parametric testing.

The paper deals with the analysis of a measurement process in the field of the variability in the measurement process. In the beginning it defines some variability sources in the measurement process, more precisely in the measurement process setting. These variability sources are then included in a controlled experiment and they are analyzed. The purpose of the paper is the evaluation which variability sources in the measurement system are really relevant from the operational measurement point of view.

This work is devoted to the analysis of measurement systems as a tool to improve the quality of measurements. Measurement System Analysis (MSA) in the sector of railway engineering is performed using the following methods: variance analysis; ranges; average and range method. A number of experiments for measuring systems are carried out with coordinate measuring machines ACCURA MASS 16/24/14 and a digital caliper. The results obtained are of universal character; and the methodology described can be applied to other measuring systems. This method is needed to quantify the measurement systems. MSA is the constituent of statistical management of processes of manufacture intended for a research of measuring processes for the purpose of an assessment of their acceptability. MSA allows drawing conclusions about the suitability of measuring processes. This gives you the opportunity to make corrective actions to improve the measuring system and, as a consequence, to guarantee the quality of the measured parameters [1, 2, 3].

The accuracy and precision of data is the most important property of electrical measurement data in the assurance of aerospace parts. Based on the basic principle of measurement system analysis, we focus on the variance method to analyze the repeatability and the reproducibility of electrical measurement data. By studying the error of the measurement system to produce, we calculate the proportion of various error sources affect the measurement result, the interaction, synthetically determination of the measurement system status and measuring data quality, and adopt effective measures to reduce or eliminate the error. With the crystal oscillator measurement system using general instrument, we carried on the practice and its help us to realize the problem of data quality. By specifying the measurement interval clearly, the specific gravity calculation results of repeatability and reproducibility are reduced from more than 70% to less than 10% of the total variation.

The decisions made in manufacturing and service settings heavily rely on the data collected through measurement systems. The main goal of measurement systems is to make sure that the data are collected through valid and reliable measurement systems. Chapter 6 focuses on how to conduct measurement system analysis in Six Sigma projects. The measurement systems are analyzed through Gage RR (2) identify and isolate the variability causes in the measurement system; and (3) evaluate if the measure system is capable, adequate, accurate, and appropriate (Montgomery, D. C., Introduction to statistical quality. Wiley, New York, 2013). The idea behind Gage R&R is to differentiate measurement system variability from process variability. Several examples are presented to demonstrate how to conduct Gage R&R analysis.

Measurement systems analysis (MSA) is a set of requirements and procedures adopted by the automotive industry and other disciplines to evaluate the accuracy and precision of measurement systems through assessing and quantifying the random and systematic errors and assigning appropriate dispositions for tolerance and performance acceptance. The methodology of variable data MSA comprises studies of a system's stability, bias, linearity and gage repeatability and reproducibility (GR&R). This paper describes advances in referencing and criteria for estimation of uncertainty errors, dispositions, and acceptability of MSA bias and linearity, proposing an extension to the basic statistical zero null-hypothesis to include overlap between confidence intervals and uncertainty associated with the reference standards used in bias and linearity studies.

To consistently produce high quality products, a quality management system must be practically implemented in every organization. One of its core instrument is to ensure the capability of the measurement systems, which are the basis for decisions regarding the behavior of the product critical quality characteristics. Base on requirements of the quality management system, a Measurement System Analysis should be conducted for all measurement system which are mentioned in the organization quality plan. Most problematic measurement system issues come from measuring discrete data, which are usually the result of human judgment (subjective decision) when categorizing products such as good/bad (visual inspection). It was the aim of this paper to address such an issue presenting a case study made in a local company from the Sibiu region, in order to evaluate how capable are the appraisers to visually inspect steel chains. The results were analyzed using MINITAB statistical software with its module called Attribute Agreement Analysis. The conclusion was that the inspection process must be improved by operator training, developing visual aids/boundary samples, establishing standards and set-up procedures.