Earticle

Designers have to consider voice of customer, process capability, manufacturing standards & condition, manufacturing method and characteristics of products to decide tolerances. Especially, in case of position of hole and pin, designers have to consider process capability to decide tolerances. The traditional position tolerances used in a drawing are theoretical values which are allocated to position under the worst case assembling condition that both hole and pin are the maximum material condition(MMC). However, when the process capability is high, more exact product size can be produced under stable manufacturing condition. Larger clearance of hole and pin can be allocated. In this point of view, manufacturer could increase the yield by allocating larger position tolerance than theoretical position tolerance of hole and pin considering process capability.

Designers have to consider voice of customer, process capability, manufacturing standards & condition, manufacturing method, characteristics of products to decide tolerances. Especially, in case of position of hole and pin, designers have to consider process capability to decide tolerances. The traditional position tolerances used in a drawing are theoretical values which are allocated to position under the worst case assembling condition that both hole and pin are the maximum material condition(MMC). However, When the process capability is high, more exact product size can be produced under stable manufacturing condition. larger clearance of hole and pin can be allocated. In this point of view, manufacturer could increase the yield by allocating larger position tolerance than theoretical position tolerance of hole and pin considering process capability.

This study analyzes the effect of Computer Aided Innovation (CAI) to improve R&D Capabilities empirically. Survey was distributed by e-mail and Google Docs, targeting CTO of 235 SMEs. 142 surveys were returned back (rate of return 60.4%) from companies. Survey results from 119 companies (83.8%) which are effective samples except no-response, insincere response, estimated value, etc. were used for statistics analysis. Companies with less than 50billion KRW sales of entire researched companies occupy 76.5% in terms of sample traits. Companies with less than 300 employees occupy 83.2%. In terms of the type of company business Partners (called 'partners with big companies' hereunder) who work with big companies for business occupy 68.1%. SMEs based on their own business (called 'independent small companies') appear to occupy 31.9%. The present status of holding IT system according to traits of company business was classified into partners with big companies versus independent SMEs. The present status of ERP is 18.5% to 34.5%. QMS is 11.8% to 9.2%. And PLM (Product Life-cycle Management) is 6.7% to 2.5%. The holding of 3D CAD is 47.1% to 21%. IT system-holding and its application of independent SMEs seemed very vulnerable, compared with partner companies of big companies. This study is comprised of IT infra and IT Utilization as CAI capacity factors which are independent variables. factors of R&D capabilities which are independent variables are organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability. The highest average value of variables was 4.24 in organization capability 2. The lowest average value was 3.01 in IT infra which makes users access to data and information in other areas and use them with ease when required during new product development. It seems that the inferior environment of IT infra of general SMEs is reflected in CAI itself. In order to review the validity used to measure variables, Factors have been analyzed. 7 factors which have over 1.0 pure value of their dependent and independent variables were extracted. These factors appear to explain 71.167% in total of total variances. From the result of factor analysis about measurable variables in this study, reliability of each item was checked by Cronbach's Alpha coefficient. All measurable factors at least over 0.611 seemed to acquire reliability. Next, correlation has been done to explain certain phenomenon by correlation analysis between variables. As R&D capabilities factors which are arranged as dependent variables, organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability turned out that they acquire significant correlation at 99% reliability level in all variables of IT infra and IT Utilization which are independent variables. In addition, correlation coefficient between each factor is less than 0.8, which proves that the validity of this study judgement has been acquired. The pair with the highest coefficient had 0.628 for IT utilization and technology-accumulating capability. Regression model which can estimate independent variables was used in this study under the hypothesis that there is linear relation between independent variables and dependent variables so as to identify CAI capability's impact factors on R&D. The total explanations of IT infra among CAI capability for independent variables such as organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability are 10.3%, 7%, 11.9%, 30.9%, and 10.5% respectively. IT Utilization exposes comprehensively low explanatory capability with 12.4%, 5.9%, 11.1%, 38.9%, and 13.4% for organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability respectively. However, both factors of independent variables expose very high explanatory capability relatively for technology-accumulating capability among independent variable. Regression formula which is comprised of independent variables and dependent variables are all significant (P < 0.005). The suitability of regression model seems high. When the results of test for dependent variables and independent variables are estimated, the hypothesis of 10 different factors appeared all significant in regression analysis model coefficient (P < 0.01) which is estimated to affect in the hypothesis. As a result of liner regression analysis between two independent variables drawn by influence factor analysis for R&D capability and R&D capability. IT infra and IT Utilization which are CAI capability factors has positive correlation to organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability with inside and outside which are dependent variables,, R&D capability factors. It was identified as a significant factor which affects R&D capability. However, considering adjustable variables, a big gap is found, compared to entire company. First of all, in case of partner companies with big companies, in IT infra as CAI capability, organization capability, process capability, human resources capability, and technology capability out of R&D capacities seems to have positive correlation. However, collaboration capability appeared insignificance. IT utilization which is a CAI capability factor seemed to have positive relation to organization capability, process capability, human resources capability, and internal/external collaboration capability just as those of entire companies. Next, by analyzing independent types of SMEs as an adjustable variable, very different results were found from those of entire companies or partner companies with big companies. First of all, all factors in IT infra except technology-accumulating capability were rejected. IT utilization was rejected except technology-accumulating capability and collaboration capability. Comprehending the above adjustable variables, the following results were drawn in this study. First, in case of big companies or partner companies with big companies, IT infra and IT utilization affect improving R&D Capabilities positively. It was because most of big companies encourage innovation by using IT utilization and IT infra building over certain level to their partner companies. Second, in all companies, IT infra and IT utilization as CAI capability affect improving technology-accumulating capability positively at least as R&D capability factor. The most of factor explanation is low at around 10%. However, technology-accumulating capability is rather high around 25.6% to 38.4%. It was found that CAI capability contributes to technology-accumulating capability highly. Companies shouldn't consider IT infra and IT utilization as a simple product developing tool in R&D section. However, they have to consider to use them as a management innovating strategy tool which proceeds entire-company management innovation centered in new product development. Not only the improvement of technology-accumulating capability in department of R&D . Centered in new product development, it has to be used as original management innovative strategy which proceeds entire company management innovation. It suggests that it can be a method to improve technology-accumulating capability in R&D section and Dynamic capability to acquire sustainable competitive advantage.

This paper presents various interval estimation methods of binomial proportion for small n in multi-product small volume production and extremely small ^P like PPM or PPB fraction of defectives. This study classifies interval estimation of binomial proportion into three categories such as exact, approximate, Bayesian methods. These confidence intervals proposed in this paper can be applied to attribute process capability and attribute acceptance sampling plan for PPM or PPB.

This paper introduce information technology of software process assessment. It consists of eight parts such as concepts and introductory guide, a reference model for processes and process capability, performing an assessment, guide to performing assessments, an assessment model and indicator guidance, guide to competency of assessors, guide for use in process improvement, and guide for use in determining supplier process capability.

New technology development capability plays a key role in making small- and medium-sized enterprises (SMEs) increase their innovation performance, such as in product or process innovation. To examine the influencing factors of SMEs' new technology development capability, this study empirically analyzes the mediating effects of SMEs' process design capability and product interior design capability on the positive association between their external information network diversity and new technology development capability. This study performs the ordinary least squares regression on a sample of 2,000 South Korean SMEs. Results reveal that SMEs' process design capability fully mediates, and product interior design capability partially mediates the positive association between the external information network diversity and new technology development capability.

본 연구는 수출 중소기업이 신규 시장을 통해 기업의 성장을 추진할 때 성과에 영향을 주는 요인을 복합적으로 분석하는데 연구 목적을 두었 다. 중소기업은 규모의 제약에 따라 성장 과정에서 정체를 겪는 경우가 많다. 이에 중소기업의 지속적 성장을 위해서는 해외시장 진출이 중요하 다는 점을 기존 연구에서 지적하였다. 본 연구에서는 이러한 기존 연구의 결과에 따라 중소기업의 확장 과정에 영향을 주는 요인을 자원기반관 점 이론을 통해서 수립하였다. 또한, 시장탐색역량 개념을 추가하여 중소기업이 보유한 자원, 역량과의 관계를 통합적으로 분석하였다. 이러한 연구 방향에 따라 중소기업의 내부자원, 내부역량, 외부 사회적 자본을 해외성과의 선행요인으로, 시장탐색역량을 매개요인으로 설정하였다. 기존 문헌 고찰을 통해 분석모형을 설정하고 수출 중소기업을 대상으로 주요 개념에 관한 조사를 수행하였다. 시장탐색역량의 매개효과를 포함 하여 8개의 가설을 설정하였으며, 159개 수출 중소기업에 대해 구조방정식모형을 활용한 PLS 분석을 시행하였다. 수출 중소기업의 기준은 전 체 매출액 대비 수출 비중이 30% 이상인 기업으로 하였다. 분석 결과 외부 사회적 자본을 제외한 중소기업의 내부자원, 내부역량, 시장탐색역량 은 모두 해외성과에 긍정적 영향을 미치는 것으로 나타났다. 반면 외부 사회적 자본은 시장탐색역량에는 긍정적 영향을 미치고 있으나 해외시 장 성과에는 유의한 결과를 보여주지 못했다. 매개효과 분석의 경우 시장탐색역량은 3개의 선행요인 중 외부 사회적 자본에 대해서만 긍정적 매 개효과를 보여주었다. 이상의 분석 결과에 따른 이론적, 실무적 시사점을 논의하였으며, 연구 한계와 향후 연구 방향을 제시하였다.

he study aimed to comprehensively analyze the factors influencing the performance of small and medium-sized enterprises (SMEs) as they pursued corporate growth through new foreign markets. Given their size constraints, SMEs often require more support in their growth processes. Existing research emphasizes the importance of SMEs entering foreign markets for sustained growth. This research built upon the findings of these studies and established factors affecting the expansion process of SMEs through the lens of resource-based perspective theory. Additionally, the study introduced the concept of market exploration capabilities to thoroughly analyze the relationship between the resources and capabilities possessed by SMEs. Following this research direction, it identified SMEs' internal resources, internal capabilities, and external social capital as leading factors influencing foreign performance, with market exploration capabilities as mediating factors. The research developed an analysis model by reviewing existing literature and surveyed fundamental concepts targeting exporting SMEs. It formulated eight hypotheses, including mediation effects, and performed a Partial Least Squares (PLS) analysis using structural equation modeling on 159 SMEs. The analysis results demonstrated that excluding external social capital, internal resources, capabilities, and market exploration capabilities all positively impacted foreign performance. In the mediation effect analysis, market exploration capability showed a positive mediation effect only on external social capital among the three preceding factors. The study discussed these results' theoretical and practical implications and concluded by considering research limitations and suggesting future research directions.

This paper considers an algorithm using Johnson transformation to calculate process capability index for non-normal distribution. Johnson transformation is well known as one of methods transforming the data with non-normal distribution to normal data.

We develop methods for propagating and analyzing EPCI(Extended Process Capability Index) by using the error type that classifies into accuracy and precision. EPCI developed in this study can be applied to the three combined processes that consist of production, measurement and calibration. Little calibration work discusses while a great deal has been studied about SPC(Statistical Process Contol) and MSA(Measurement System Analysis). EPCI can be decomposed into three indexes such as PPCI(Production Process Capability Index), PPPI(Production Process Performance Index), MPCI(Measurement PCD, and CPCI(Calibration PCI). These indexs based on the type of error classification can be used with various statistical techniques and principles such as SPC control charts, ANOVA(Analysis of Variance), MSA Gage R&R, Additivity-of-Variance, and RSSM(Root Sum of Square Method). As the method proposed is simple, any engineer in charge of SPC. MSA and calibration can use efficientily in industries. Numerical examples are presentsed. We recommed that the indexes can be used in conjunction with evaluation criteria.

소프트웨어 고장 시간은 테스팅 시간과 관계없이 일정하거나. 단조증가 혹은 단조 감소 추세를 가지고 있다. 이러한 소프트웨어 신뢰모형들을 분석하기 위한 자료척도로 자료에 대한 추세 검정이 개발되어 있다. 추세 분석에는 산술평균 검정과 라플라스 추세 검정등이 있다. 추세분석들은 전체적인 자료의 개요의 정보만 제공한다. 이러한 분석도구를 다시 세분화하여 품질 관리 측면에서 분석을 시도 할 필요가 있다. 따라서 본 논문에서는 품질관리 측면에서 사용되는 공정능력지수를 이용한 공정분석을 시도하였다. 소프트웨어 고장 간격 시간은 비음이기 때문에 수명분포가 정규분포를 가정하는 기존의 공정능력분석방법 대신에 정규화 시켜주는 박스-코스 변환을 이용하여 공정 능력 분석을 시도 하였다. 공정능력에 사용된 고장 간격 시간자료는 실제 자료인 SS3을 이용하였고 그 결과를 나열 하였고 이런 결과들의 활용 방안을 제시 하였다.

Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analy-sis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. From the subdivision of this analysis, new attemp needs the side of the quality control. In this paper, we discuss process capability analysis using process capability indexs. Because of software failure interval time is pattern of nonnegative value, instead of capability analysis of suppose to normal distribution, capability analysis of process distribution using to Box-Cox transformation is attermpted. The used software failure time data for capability analysis of process is SS3, the result of analysis listed on this chapter 4 and 5. The practical use is presented.

Process capability indices are widely used in industries and quality assurance system. When designing the parameter on the multiple quality characteristics, there has been a study for optimization of problems, but there has been few former study on the possible conflicting phenomena in considertion of the correlations among the characteristics. To solve the issue on the optimal design for muliple quality characteristics, the study propose the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of terms. Therefore, the analysis have to be required a multivariate statistical technique. This paper introduces to multivariate capability indices and then selects a multivariate process capability index incorporated both the process variation and the process deviation from target among these indices under the multivariate normal distribution. We propose a new multivariate capability index MCpm using quality loss function instead of the process variation and this index is compared with the proposed indices when quality characteristics are independent and dependent of each other,

It is necessary to deal with the process capability index carefully because it has been developed with certain assumptions. Companies make a decision on processes through the results obtained by using and treating data extracted from the processes. However if they have incorrect or wrong results, they cannot lead to proper outputs but also bring to loss of the competition in quality. Therefore, this study will show a method to analysis Cp (process capability ; CP) and an idea of mass-production on Pp (process performance ; PP) based on the Sigma Estimate which is one of the uncertainty in the process capability index and makes a lot of error. To apply this method, it is essential to understand and to analyze the processes exactly. Especially, it is required to establish the more accurate process capability index that can quickly and properly respond to changes on processes to recognize the small changes on the process which lies in specification in mass production system that the continual monitoring of quality managers is required.

As we understand it, Process Capability indices are intended to provide single-number assessments of ability to meet specification limits on quality characteristics of interest. As a consequence of the varied ways in which PCIs are used, there have been two natural lines of research work: ① studies on the properties of PCIs and their estimators in many different environments; ② construction of new PCIs purporting to have better properties in certain circumstances. The most of existing process capability indices are concerned with the single variable. But, in many cases, a quality characteristic is composed with several factors. In that case, we want to know the integrated process capability of a quality characteristic not those of each factor. In this paper, we proposed a new multivariate system process capability index called MSPCI:SCpsk which is the geometric mean of performance measure Cpsk.'S, and will be used as the criterion to assess multiple response process designs. Numerical illustration is done for SCpsk, Cp(f), Cp, Cpk, Cpm, and Cpsk.

1980년대 초기 미 국방성에서는 소프트웨어 개발업체의 소프트웨어 개발능력에 대한 판단 착오로 금전적, 시간적, 성능상의 많은 어려움을 겪어왔다. 따라서 미 국방성은 카네기 멜론 대학의 SEI(Software Engineering Institute)를 통하여 소프트웨어 개발능력을 측정하고, 조직의 소프트웨어 프로세스 성숙수준을 결정하기 위한 CMM(Capability Maturity Model)을 개발하였다. 그러나 CMM에 기반을 둔 소프트웨어 프로세스 평가 방법은 외부 전문가를 이용하여 평가하므로, 시간과 비용이 많이 소모되는 방법이다. 따라서 많은 기업에서 이러한 평가를 수행하는데 어려움을 느끼고 있다. 특히, 중ㆍ소규모의 조직에서 사용하기에는, CMM의 평가방법은 너무 복잡하고 추상적이다. 소규모 기업의 경우에 3년여에 걸친 프로세스 향상노력으로 많은 성과가 이루어 졌음에도 불구하고 CMM의 평가방법을 이용한 결과는 1 단계 수준을 벗어나지 못하였다는 사례들이 많이 발표되고 있다. 이러한 결과들은 CMM의 평가 방법은 중소 규모 조직에는 적절치 않다는 것을 입증한다. 따라서 중소 규모 기업이나 조직의 소프트웨어 프로세스의 성숙도 평가와 개선을 위한 모델들을 개발하기 위한 노력이 전 세계적으로 광범위하게 펼쳐지고 있다. 본 연구에서는 최근의 모델인 CMMI(Capability Maturity Model Integration)의 소프트웨어 프로세스 영역 분류에 의거해서, 우리나라의 소프트웨어의 개발과 취득에 관련된 조직들이 각 프로세스 영역을 얼마나 중요하게 평가하는지, 그리고 해당 영역에서의 기준, 절차 그리고 방법을 문서화시키는 것을 얼마나 중요하게 평가하는지를 조사하였다. 한국의 소프트웨어 개발 관행은 CMM이나 ISO Is504 등에서 바람직한 것으로 제시하고 있는 국제 표준과는 많이 다르며, 나아가서는 예를 들어, 미국의 일반적인 관행과도 많이 다를 수 있다. 따라서 미국이나 유럽의 대규모 소프트웨어 조직을 위해서 개발된 CMM이나 ISO 15504 등은 우리나라의 중소 규모 소프트웨어 조직에는 특히 부적절할 수 있다 본 연구에서는 우리나라 소프트웨어 조직의 종류, 조직의 규모, 그리고 프로젝트 수행 규모에 따라서 각 소프트웨어 프로세스 영역의 중요도가 어떻게 다른지, 그리고 해당 소프트웨어 프로세스 영역의 기준, 절차 그리고 방법을 문서화시킬 필요성이 어떻게 변하는가를 조사하였다. 본 연구 결과는 우리나라의 소프트웨어 조직들이 프로세스 개선을 위해서 무엇을 정말로 필요로 하는지를 밝힘으로써, 한국 소프트웨어 산업의 현실적인 특수성을 고려한 소프트웨어 프로세스 평가와 개선 모델의 개발을 위한 기초적인 자료를 제공할 것으로 예상된다 또한, 본 연구 결과는, 우리나라 소프트웨어 조직들이 실제로 무엇을 필요로 하는지를 밝힘으로써, 우리나라의 소프트웨어 산업을 육성하기 위한 실효성 있는 정책 입안을 위한 기초 자료를 제공할 것으로 예상된다.

Process capability indices are widely used in industries and quality assurance system. When designing the parameter on the multiple quality characteristics, there has been a study for optimization of problems, but there has been few former study on the possible conflicting phenomena in considertion of the correlations among the characteristics. To solve the issue on the optimal design for multiple quality characteristics, the study propose the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of terms. Therefore, the analysis have to be required a multivariate statistical technique. This paper introduces to multivariate capability indices and then selects a multivariate process capability index incorporated both the process variation and the process deviation from target among these indices under the multivariate normal distribution. We propose a new multivariate capability index MCpm using quality loss function instead of the process variation and this index is compared with the proposed indices when quality characteristics are independent and dependent of each other.

We propose, a new process capability index Cpik (WV) applying the weighted variance control charting method for non-normally distributed. The main idea of the weighted variance method(WVM) is to divide a skewed or asymmetric distribution into two normal distributions from its mean to create two new distributions which have the same mean but different standard deviations. In this paper we propose an example, a distributions generated from the Johnson family of distributions, to demonstrate how the weighted variance-based process capability indices perform in comparison with another two non-normal methods, namely the Clements and the Wright methods. This example shows that the weighted valiance-based indices are more consistent than the other two methods in terms of sensitivity to departure to the process mean/median from the target value for non-normal processes. Second method show using the percentage nonconforming by the Pearson, Johnson and Burr systems. This example shows a little difference between the Pearson system and Burr system, but Johnson system underestimated than the two systems for process capability.

The main objective of this paper is to propose a measure of evaluation for non-normal process capability. If a process is not normally distributed, but normal-based techniques are used, serious errors can result. Our approach to solve this problem is that the Pearson system, the Johnson system, and the Burr system are selected for estimating a measure of process capability using the percentage nonconforming. In this paper, we found that the Pearson system and the Johnson system were a conparatively reasonable methods to calculate out of specification by example.