The process control methods based on the statistical analysis apply the analysis method or mathematical model under the assumption that the process characteristic is normally distributed. However, the distribution of data collected by the automatic measurement system in real time is often not followed by normal distribution. As the statistical analysis tools, the process capability index (PCI) has been used a lot as a measure of process capability analysis in the production site. However, PCI has been usually used without checking the normality test for the process data. Even though the normality assumption is violated, if the analysis method under the assumption of the normal distribution is performed, this will be an incorrect result and take a wrong action. When the normality assumption is violated, we can transform the non-normal data into the normal data by using an appropriate normal transformation method. There are various methods of the normal transformation. In this paper, we consider the Box-Cox transformation among them. Hence, the purpose of the study is to expand the analysis method for the multivariate process capability index using Box-Cox transformation. This study proposes the multivariate process capability index to be able to use according to both methodologies whether data is normally distributed or not. Through the computational examples, we compare and discuss the multivariate process capability index between before and after Box-Cox transformation when the process data is not normally distributed.

Recently, the manufacturing process system in the industrial field has become more and more complex and has been influenced by many and various factors. Moreover, these factors have the dependent correlation rather than independent of each other. Therefore, the statistical analysis has been extended from the univariate method to the multivariate method. The process capability indices have been widely used as statistical tools to assess the manufacturing process performance. Especially, the multivariate process indices need to be enhanced with more useful information and extensive application in the recent industrial fields. The various multivariate process capability indices have been studying by many researchers in recent years. Hence, the purpose of the study is to compare the useful and various multivariate process capability indices through the simulation. Among them, we compare the useful models of several multivariate process capability indices such as MCpm, MC+pm and MCpl. These multivariate process capability indices are incorporates both the process variation and the process deviation from target or consider the expected loss caused by the process deviation from target. Through the computational examples, we compare these process capability indices and discuss their usefulness and effectiveness.

Process Capability (Cpk) is a representative measure of how well the producer manages dispersion and bias for the specifications needed by the consumer. This is expressed as a ratio of 6 times the natural tolerance to the specification. As the producer manages the dispersion small, the capacity index becomes higher. And it is classified into 5 grades according to the degree of management. It is a measure of the quality of processes used in most industrial fields. However, Cpk is calculated by only reflecting the mean and dispersion of the process, there is a disadvantage that it can not give information about the economic loss caused by the inconsistency of the process with the target value. Overcoming these drawbacks, process capability indexes reflecting various types of loss functions such as Cpm, C┼pm and Cpl have been developed. However, all of these previous studies have applied the limit to the consumer specification, which is based on the traditional and passive quality perception that the quality characteristic should exist within the limits of the consumer specification. In this study, we will develop ‘Customer Satisfaction Quality Indicator (CSQI)’ which is a quantitative indicator that can be fully evaluated when the manufacturer’s specification limit, which is an aggressive quality strategy, is applied. This is expected to be useful decision information for both producers and consumers.

Taguchi regarded the concept of quality as ‘total loss to society due to fluctuations in quality characteristics from the time of supplied to the customer.’ The loss function is a representative tool that can quantitatively convert the loss that occurs due to the deviation of the quality characteristic value from the target value. This has been utilized in various studies with the advantage that it can change the social loss caused by fluctuation of quality characteristics to economic cost. The loss function has also been used extensively in the study of producer specification limits. However, in previous studies, only the second order loss function of Taguchi is used. Therefore, various types of losses that can occur in the process can’t be considered. In this study, we divide the types of losses that can occur in the process considering the first and second loss functions and the Spiring’s reflected normal loss function, and perform total inspection before delivering the customer to determine the optimal producer specification limit that minimizes the total cost. Also, we will divide the quality policy for the products beyond the specification limits into two. In addition, we will show the illustration of expected loss cost change of each model according to the change of major condition such as customer specifications and maximum loss cost.

In the industrial fields, the process capability index has been using to evaluate the variation of quality in the process. The traditional process capability indices such as Cp, Cpk, Cpm, and C┼pm have been applied in the industrial fields. These traditional process capability indices are mainly applied in the univariate analysis. However, the main streams in the recent industry are the multivariate manufacturing process and the multiple quality characteristics are corrected each other. Therefore, the multivariate statistical method should be used in the process capability analysis. The multivariate process indices need to be enhanced with more useful information and extensive application in the recent industrial fields. Hence, the purpose of the study is to develop a more effective multivariate process index (MCpI ) using the multivariate inverted normal loss function. The multivariate inverted normal loss function has the flexibility for the any type of the symmetrical and asymmetrical loss functions as well as the economic information. Especially, the proposed modeling method for the multivariate inverted normal loss function (MINLF) and the expected loss from MINLF in this paper can be applied to the any type of the symmetrical and asymmetrical loss functions. And this modeling method can be easily expanded from a bivariate case to a multivariate case.

Recently, service quality must reflect several demands of customers who show rapid and various changes so as to be compared with the past. So, objective and rapid measuring methods for service quality are necessary. For them, first of all, service company must calculate their standard of service quality accurately by measuring service quality exactly. Kano classified the degree of influence that is the degree of correspondence of the quality attributes of products and services to the subjective satisfaction of customers. As a result, the types of qualities are classified as attractive, must be, one dimensional, and indifference attributes. They have been widely used quality attributes in various industrial fields up to now. However, Kano model has a limit that it ignores the characters of the next frequent numbers even though there are not much gap comparing to the most frequent number in the questionnaire answers. The limit is attributed to the character of Kano model that the most frequent number is accepted as the only quality character. Timko calculated the customer satisfaction coefficient by using Kano’s method and studied the differences in quality character by classifying the quality characteristics in a graphical way through the relationship between the satisfaction and the dissatisfaction coefficient. In this study, we used the quality level determination method of the 7-point Likert scale, which takes the weight into account, to complement the deficiencies of the existing Kano model. We also developed and applied a Potential Satisfaction Level (P) and Potential Customer Demand Improvement (PCDI) Index to present a new approach to the determination of service quality attributes. To measure the level of potential service satisfaction and to understand the degree of improvement, we collected specimens of 51 participants who has been trained in the National Strategy Business Training Program, which has been managed by government agent, and analyzed the results.1)

Climate change is the biggest environmental issue of our times. A variety of activities to reduce greenhouse gas emissions have been in progress to observe the Kyoto Protocol. Especially, the Energy Target Scheme is created to reduce greenhouse emission with the supervision of Korean government. This includes Green-house Gas Information Systems to promote activities in the private sector to reduce green-house gas emissions, to cut a cost of energy use, and to reduce GHG emissions. Also, the system has calculated the amount of greenhouse gases. Without any additional investment, 2.75% savings are increased over the previous year. In service sector, a cooperation of customers and employees is necessary. A reduction of GHG emissions requires a proper service organization, considering an amount of investment and payback period. Without any additional investment or replacement, employees can save energy easily turning off ventilation systems an hour before employees’ departure, installing timers to turn off water purifiers and vending machines after some period of no use. The Green-house Gas Information System is similar to that of Environmental Management System. However, the Excel is the best program to calculate an amount of green-house gas emissions, and to assess for a reduced amount of GHG emissions. A goal of this research is to propose a practical method in the private sector to calculate an amount of green-house gases. The Green-house gas Information System based on Excel spreadsheet gives standards for good evaluation. The greenhouse gas information system establishes and executes the policies and objectives related to greenhouse gas emissions Similar to ISO 14001 environment management system structures, the advantages of using simplified Excel Sheet for calculating GHG emissions and reducing GHG emissions are easy to access.

A one-shot system (device) refers to a system that is stored for a long period of time and is then disposed of after a single mission because it is accompanied by a chemical reaction or physical destruction when it operates, such as shells, munitions in a defense weapon system and automobile airbags. Because these systems are primarily related with safety and life, it is required to maintain a high level of storage reliability. Storage reliability is the probability that the system will operate at a particular point in time after storage. Since the stored one-shot system can be confirmed only through inspection, periodic inspection and maintenance should be performed to maintain a high level of storage reliability. Since the one-shot system is characterized by a large loss in the event of a failure, it is necessary to determine an appropriate inspection period to maintain the storage reliability above the reliability goal. In this study, we propose an optimal inspection policy that minimizes the total cost while exceeding the reliability goal that the storage reliability is set in advance for the one-shot system in which periodic inspections are performed. We assume that the failure time is the Weibull distribution. And the cost model is presented considering the existing storage reliability model by Martinez and Kim et al. The cost components to be included in the cost model are the cost of inspection c1, the cost of loss per unit time between failure and detection c2, the cost of minimum repair of the detected breakdown of units c3, and the overhaul cost c4 of  ≤ . And in this paper, we will determine the optimal inspection policy to find the inspection period and number of tests that minimize the expected cost per unit time from the finite lifetime to the overhaul. Compare them through numerical examples.

As the functions and structure of the system are complicated and elaborated, various types of structures are emerging to increase reliability in order to cope with a system requiring higher reliability. Among these, standby systems with standby components for each major component are mainly used in aircraft or power plants requiring high reliability. In this study, we consider a standby system with a multi-functional standby component in which one standby component simultaneously performs the functions of several major components. The structure of a parallel system with multifunctional standby components can also be seen in real aircraft hydraulic pump systems and is very efficient in terms of weight, space, and cost as compared to a basic standby system. All components of the system have complete operation, complete failure, only two states, and the system has multiple states depending on the state of the component. At this time, the multi-functional standby component is assumed to be in a non-operating standby state (Cold Standby) when the main component fails. In addition, the failure rate of each part follows the Weibull distribution which can be expressed as increasing type, constant type, and decreasing type according to the shape parameter. If the Weibull distribution is used, it can be applied to various environments in a realistic manner compared to the exponential distribution that can be reflected only when the failure rate is constant. In this paper, Markov chain analysis method is applied to evaluate the reliability of multi-functional multi-state standby system. In order to verify the validity of the reliability, a graph was generated by applying arbitrary shape parameters and scale parameter values through Excel. In order to analyze the effect of multi-functional multi-state standby system using Weibull distribution, we compared the reliability based on the most basic parallel system and the standby system.

Climate change has been identified as one with the greatest challenges facing nations, government, business and over future decades. Activities to reduce greenhouse gas emissions by the Kyoto Protocol, the international community has been in progress. Korea also has introduced the Emission trading system to reduce greenhouse emission from the supervision of the government. Greenhouse gases emissions quantity should be internationally recognized. Mutual Recognition Arrangement should be recognized as the same greenhouse gas emission. International recognition of domestic verification body of international mutual recognition is required. Efforts are needed to secure the equivalence between the emission rights through direct cooperation with the relative nation accreditation body. Early entry into the IAF/PAC GHG MLA is essential for demonstrating equivalence between greenhouse gas emissions. Emissions trading will also require connection to the EU ETS, California, USA, and Tokyo, Japan to link Emissions trading. In the case of establishing accreditation standards and accreditation criteria, it will be necessary to distinguish between the domestic Energy Target Management System and the Emission Trading System. Independent greenhouse gases verification bodies should be established to meet the requirements of IAF and PAC. It is necessary to revise the qualification criteria for the verification of the greenhouse gas verification body according to international standards requirements. It is necessary to support the role of accreditation bodies of domestic greenhouse gas verification bodies. It is required to join international organizations of international mutual recognition of international trade and the need for pilot projects to link greenhouse gas emissions. The core link to our emission trading system is called EU-ETS, and we will need to join the IAF/PAC GHG MLA GHG. The International Mutual Recognition Agreement (IAF) is expected to allow international interoperability of GHG emissions verification between EA and the PAC. By signing a PAC GHG MLA, it will need to be prepared to prepare for the pilot project to link the emission trading system.

Process quality control, which prevents problems and risks that may occur in products and processes, has been recognized as an important issue, and SPC techniques have been used for this purpose. Process Capability Index (PCI) is useful Statistical Process Control (SPC) tool that is measure of process diagnostic and assessment tools widely use in industrial field. It has advantage of easy to calculate and easy to use in the field. Cp and Cpk are traditional PCIs. These traditional Cp and Cpk were used only as a measure of process capability, taking into account the quality variance or the bias of the process mean. These are not given information about the characteristic value does not match the target value of the process and this has the disadvantage that it is difficult to assess the economic losses that may arise in the enterprise. Studies of this process capability index by many scholars actively for supplement of its disadvantage. These studies to evaluate the capability of situation of various field has presented a new process capability index. Cpm is considers both the process variation and the process deviation from target value. And Cpm + is considers economic loss for the process deviation from target value. In this paper we developed an improved Expected Loss Capability Index using Reflected Normal Loss Function of Spring. This has the advantage that it is easy to realistically reflect the loss when the specification is asymmetric around the target value. And check the correlation between existing traditional process capability index (Cpk) and new one. Finally, we propose the criteria for classification about developed process capability index.

Control Chart is a graph which dots the characteristic values of a process. It is the tool of statistical technique to keep a process in controlled condition. It is also used for investigating the state of a process. Therefore many companies have used Control Chart as the tool of statistical process control (SPC). Products from a production process represent accidental dispersion values around a certain reference value. Fluctuations cause of quality dispersion is classified as a chance cause and a assignable cause. Chance cause refers unmanageable practical cause such as operator proficiency differences, differences in work environment, etc. Assignable cause refers manageable cause which is possible to take actions to remove such as operator inattention, error of production equipment, etc. Traditionally x-R control chart or x-s control chart is used to find and remove the error cause. Traditional control chart is to determine whether the measured data are in control or not, and lets us to take action. On the other hand, RNELCC (Reflected Normal Expected Loss Control Chart) is a control chart which, even in controlled state, indicates the information of economic loss if a product is in inconsistent state with process target value. However, contaminated process can cause control line sensitive and cause problems with the detection capabilities of chart. Many studies on robust estimation using trimmed parameters have been conducted. We suggest robust RNELCC which used the idea of trimmed parameters with RNEL control chart. And we demonstrate effectiveness of new control chart by comparing with ARL value among traditional control chart, RNELCC and robust RNELCC.

Control chart is representative tools of statistical process control (SPC). It is a graph that plotting the characteristic values from the process . It has two steps (or Phase). First step is a procedure for finding a process parameters. It is called PhaseⅠ. This step is to find the process parameters by using data obtained from in-controlled process. It is a step that the standard value was not determined. Another step is monitoring process by already known process parameters from PhaseⅠ. It is called Phase Ⅱ. These control chart is the process quality characteristic value for management, which is plotted dot whether the existence within the control limit or not. But, this is not given information about the economic loss that occurs when a product characteristic value does not match the target value. In order to meet the customer needs, company not only consider stability of the process variation but also produce the product that is meet the target value. Taguchi’s quadratic loss function is include information about economic loss that occurred by the mismatch the target value. However, Taguchi’s quadratic loss function is very simple quadratic curve. It is difficult to realistically reflect the increased amount of loss that due to a deviation from the target value. Also, it can be well explained by only on condition that the normal process. Spiring proposed an alternative loss function that called reflected normal loss function (RNLF). In this paper, we design a new control chart for overcome these disadvantage by using the Spiring’s RNLF. And we demonstrate effectiveness of new control chart by comparing its average run length (ARL) with x-R control chart and expected loss control chart (ELCC).

In the manufacturing industry fields, thousands of quality characteristics are measured in a day because the systems of process have been automated through the development of computer and improvement of techniques. Also, the process has been monitored in database in real time. Particularly, the data in the design step of the process have contributed to the product that customers have required through getting useful information from the data and reflecting them to the design of product. In this study, first, characteristics and variables affecting to them in the data of the design step of the process were analyzed by decision tree to find out the relation between explanatory and target variables. Second, the tolerance of continuous variables influencing on the target variable primarily was shown by the application of algorithm of decision tree, C4.5. Finally, the target variable, loss, was calculated by a loss function of Taguchi and analyzed. In this paper, the general method that the value of continuous explanatory variables has been used intactly not to be transformed to the discrete value and new method that the value of continuous explanatory variables was divided into 3 categories were compared. As a result, first, the tolerance obtained from the new method was more effective in decreasing the target variable, loss, than general method. In addition, the tolerance levels for the continuous explanatory variables to be chosen of the major variables were calculated. In further research, a systematic method using decision tree of data mining needs to be developed in order to categorize continuous variables under various scenarios of loss function.

Recently, the production cycle in manufacturing process has been getting shorter and different types of product have been produced in the same process line. In this case, the control chart using coefficient of variation would be applicable to the process. The theory that random variables are located in the three times distance of the deviation from mean value is applicable to the control chart that monitor the process in the manufacturing line, when the data of process are changed by the type of normal distribution. It is possible to apply to the control chart of coefficient of variation too.  ,  estimates that taken in the coefficient of variation have just used all of the data, but the upper control limit, center line and lower control limit have been settled by the effect of abnormal values, so this control chart could be in trouble of detection ability of the assignable value. The purpose of this study was to present the robust control chart than coefficient of variation control chart in the normal process. To perform this research, the location parameter, xα, sα were used. The robust control chart was named Tim-CV control chart. The result of simulation were summarized as follows; First, P values, the probability to get away from control limit, in Trim-CV control chart were larger than CV control chart in the normal process. Second, ARL values, average run length, in Trim-CV control chart were smaller than CV control chart in the normal process. Particularly, the difference of performance of two control charts was so sure when the change of the process was getting to bigger. Therefore, the Trim-CV control chart proposed in this paper would be more efficient tool than CV control chart in small quantity batch production.

Due to advancements in technology and manufacturing capability, it is not uncommon that life tests yield no or few failures at low stress levels. In these situations it is difficult to analyse lifetime data and make meaningful inferences about product or system reliability. For some products or systems whose performance characteristics degrade over time, a failure is said to have occurred when a performance characteristic crosses a critical threshold. The measurements of the degradation characteristic contain much useful and credible information about product or system reliability. Degradation measurements of the performance characteristics of an unfailed unit at different times can directly relate reliability measures to physical characteristics. Reliability prediction based on physical performance measures can be an efficient and alternative method to estimate for some highly reliable parts or systems. If the degradation process and the distance between the last measurement and a specified threshold can be established, the remaining useful life is predicted in advance. In turn, this prediction leads to just in time maintenance decision to protect systems. In this paper, we describe techniques for mapping product or system which has degrading performance parameter to the associated classical reliability measures in the performance domain. This paper described a general modeling and analysis procedure for reliability prediction based on one dominant degradation performance characteristic considering pseudo degradation performance life trend model. This pseudo degradation trend model is based on probability modeling of a failure mechanism degradation trend and comparison of a projected distribution to pre-defined critical soft failure point in time or cycle.

ISO 9001, quality management system, is widely known as advancing internal efficiency and productivity in various industry. As a result, the number of companies that have adopted ISO 9001’s certification have been increasing continuously year by year since ISO 9000’ family standard was published in 1987s. This fact shows that a lot of businesses are trying to get the accreditation for improving the competitiveness of quality. The purpose of this study is to present that ISO 9001’s certification motives affect to the requirement’s implementation and show that the execution of requirements influences on management performance in the small manufacturer. In order to carry out this research, we obtained 96 survey sheets and inspected twenty assumptions based on the reliability, validity of the questionnaires. The results of regression analysis are summarized as follows; First, the factors of certification motive influence on the requirement’s implementation except resources management. Second, the two elements of ISO 9001 requirement, resources management and product realization, have an important effect on the operational performance and financial performance considerably in the companies that choose the internal motive. Finally, the two requisites of ISO 9001 requirement, resources management and measurement, analysis and improvement, affect to the operational performance and financial performance significantly in the businesses that select the external motive. Based on the results, the companies that choose the internal motive have a good performance to execute the ISO 9001 requirements. Also, to implement the requirements of ISO 9001 is helpful for the companies to produce the operational and financial performance.

Control charts are generally used for process control, but the role of traditional control charts have been limited in case of a non-contaminated process. Traditional x-s control chart has not been activated well for such a problem because of trying to control processes as center line and control limits changed by the contaminated value. This paper suggests modified x-s control chart based on robust estimation. In this paper, we consider the trimmed mean of the sample means and the trimmed mean of the sample standard deviations. By comparing with ARL value, the responding results are decided. The comparison resultant results of traditional control chart and modified control chart are contrasted.

The purpose of this study is to introduce a empirical study of using Taguchi Method for the Entrepreneurial Orientation and Financial Performance. In this study, three factors of Entrepreneurial Orientation, innovation, pro-activity and risk taking, are used of the control factors and an element, period of establishment, is chosen as a noise factor. In order to carry out this research, we obtained 200 survey sheets and performed the reliability and validity analysis of the questionnaires and then the experiment was conducted by Taguchi's experimental design. To improve Financial Performance under the noise factor of period of establishment, optimal condition are as follows; the two factors of Entrepreneurial Orientation, innovation, pro-activity should be maintained to a high level. Also, other factor, risk taking should be performed as the level that the company has maintained. Through this paper, we find out that Taguchi method is applicable for analysis of questionnaire.