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The Research of Multivariate Quality Management MA Hui, CHEN Xiangcui Information College, Capital University of Economics and Business, P.R.China, 100070 [email protected] Abstract The concept of supply chain management involves a number of suppliers, factories, distributors and customers. It is remarkable that, those management activities, on which the value chain focuses , such as internal and external logistics, are also factors of the field of quality management. Meanwhile, it has become a trend to develop a closed working relationship with the suppliers. The more "chaotic" the vendor’s quality is, the more interruptible the supply will be. Due to the quality of the supplier management is not matching with the enterprise management level, the effect of other quality management will be undermined greatly, which forms the bottleneck of quality. So, in the environment of multivariate quality management, the matching of quality in the management of the value chain has become an important task. Keywords: Multivariate quality management, Supply chain management, Data mining 1 Introduction With the importance of quality understood by people, the seeking for the ways to approach the quality requirements is also boosting up. The outcomes of quality research masters and practitioners from different countries have greatly promoted the development of quality management. And they provide comprehensive and localized theories, methods, tools, and models to achieve quality goals. It is not exaggerated that these above have played important roles in the quality practice during the past ten years. It is more important that all of these provide, to the leaders at all levels, the evidences of "we can do" and very detailed road maps to achieve the quality goals. As well, all kinds of international quality standards and quality management strategies derived provide a driving force for software quality movement. The "SanLu" event, a quality issue on milk, leads to the collapse of the milk enterprise group. In addition, it also affects agriculture (especially dairy farmers), industry (especially food industry), as well as health care, early childhood education, social psychology, foreign-related disputes, the international credibility...etc. Also, the extent of the losses and deep influence it caused could be described in a Chinese idiom” Too numerous to record”. At nearly the same time, the success of “the 29th Beijing Olympic Games” and “Paralympic Games" and lifting off of the “Shenzhou Seven” spacecraft and the maiden spacewalk of Zhigang Zhai, witness the success in quality management. We have been engaged in quality work for several decades, spending most of our time at the front line of project development, dedicated in large and small software development projects. Sometimes, we evaluate and diagnose many software projects as CMMI director evaluators. Through in-depth analysis of these projects, I fully realize that the software development is the kind of difficult and special activities, which still mainly rely on the experience up to now. The prime causes of this situation are from two aspects: inner and external. The management of large-scale knowledge work is facing unprecedented challenges. The external environment of project development also causes more various complicated factors to such kind of researching. We are also exploring how to manage the large-scale knowledge working both effectively and efficiently. In our practice, we find that the typical problems in project management mainly include: delay of product delivery, unexpected expansion of project scale and increasing cost, inability to meet the demand of customers for products, poor quality of subcontractors and the weakness, disorder and loopholes that they aroused, and also inability to control the entire project. According to Table 1, all these common problems in software management fall into three groups: 1) resources or cost, 2) progress, and 3) quality. 904 Table 1 Common Problems in Software Management Problem classification Typical problem description Cost / budget problem Resource (cost) The use of computer resource problem problem The problem of the distribution of personnel / employee …… Problem of develop plan Problem of test progress Problem of increase progressively and modify progress Progress problem The problem of milestone The problem of productivity …… Weak in configuring management Mistake catch demand Wrong structure design Wrong coding management Wrong test design scheme Wrong conversion way Manage quality problem Weak in training management Mistake increase progressively and modify management Weak subcontract management Lack the base line management …… 2 The Research on Knowledge System of Quality Management Compared with an unstable production process, a stable production process in statistical control has many advantages. The progress of information technology and the development of user service continuously put forward a various new demands for existing quality management. This requires to break the existing quality management structures, and injects new contents to quality management theories, methods, tools and rules constantly. The no longer existing of the obstacle on space for people and the large amount of various kind of new elements which covering broad areas lead to such a situation: On the one hand, there are without number of ‘panaceas’ on quality management, which change quickly; on the other hand, it is hard to find with what people could start and leaves people feeling that they can do nothing but nail biting. Facing so many elements related to software quality management such as the new environment of economic globalizing, quality culture, the tools of statistical quality control, CMMI Capability Maturity Model Integration , 6σ, subcontracting, economic analysis of information resources allocation, and so on, people will rethink that what is the main line to ensure product quality? What is the minimum standard of quality management? What belongs to the uneconomical “excessive management”? What is gradually improved road map? And what is the key management template and tool? In fact, to answer these questions above can not void a core work as the research of knowledge systems. As we all know, the job of researching knowledge system is tough. And at the early years of quality management, there is little attention payed on it, due to less jobs on it. However, with the software quality management and technology developing rapidly, people have become more and more expected to the integration of knowledge. So we can even say, the research and practice of knowledge system gradually become as important as the developing new measures, or even more important than it. It could be understood in this way, we prefer to say that the understanding and choice of ideas, methods and rules as well as the comprehensive management needs the guidance of knowledge system more urgently other than the importance of establishing knowledge system. Although the knowledge concerning quality management is complex and in constant change and development, its internal objective law of development still exist. We analyse and sort out the relative ( ) 905 knowledge of quality management, integrate its ideas, principles, civilization environments, tools and methods, master the points of quality management and pay attention to the tendency of its development so as to make us to do what should do, and get benefit. Considering the feature of software, understanding the necessity of establishing the evaluation model of software quality management and with the close relationship between international subcontracting market and quality evaluation, it make us further understanding of positive effect of implementing software quality evaluation. 1) The rules and research of software quality management Research on the rules, including investigation of background, risk and commercial target; Research on relative subjects, such as quality management, management, engineering, managerial economics; Research on development and so on. 2) Research on the engineering of software Research on measurement and control of statistical process, quality capacity management, and so on 3) Economic analysis of software management Marginal benefit analysis of quality management investment Efficiency analysis, including anti-standardization and the issues on coupling, and so on 4) Quality standard ISO 9000 quality standards, 6σ quality standards and implementation, CMMI software mature capacity model, internal audit, external evaluation, subcontract ranking Quality management tools, including VSS, Minitab and so forth. 3 Research on Multivariate Quality Matching and Discrimination What the quality value chain concerns are not only internal management link, but also quality activities of upstream and downstream and management activities of the production, referring to the quality of the entire chain. the economic environment of globalization, the improvement of quality culture, the role of quality certification and the cost of quality management activities should be considered, as well as the quality analysis under globalization environment, supplier quality management, quality culture construction, qualitative and quantitative management, standard, subcontractors’ management, and so on. Figure 1 The Quality Analysis under The Global Chain Based on the idea of quality management chain, quality management activities mainly include: The evaluation of every link of quality management, including the assessment of the quality of supplier management; 906 The comparison and analysis of the quality level; The improvement and feedback, and so on. Figure 2 Quality analysis and matching variation The quantification of the matching level of the quality chain is the key point to evaluate and solve the problem. The following two indexes are used: process capability index Cp (describing the “slender degree” and the stability) and process capability index Cpk describing the deviation and “aiming degree” . CP is the abbreviation for Process Capability Index in English, translated as the process capability index. Process Capability Index refers to the actual processing capacity of the process at a certain time and in control state (steady state). It is the natural ability of the process, or it is the ability of process for quality assurance. The higher the process capability is, the smaller the dispersion of the sample’s quality characteristic value will be; the lower the process capability is, the bigger the dispersion of the sample’s quality characteristic value will be. No deviational Cp express uniformity (stability) of the course of processing, that is "the quality of capacity", the bigger Cp is, the “slimmer” the distribution of the quality characteristics will be, and the stronger the quality capacity will be. When deviation exits between the distribution centre and tolerance centre, the process capability index is recorded as Cpk. The deviated Cpk stands for the deviation between the distribution centre µ and tolerance centre M. The bigger Cpk is, the smaller the deviation will be, that is, the process centre is more “targeted” to the tolerance. The emphases of Cp and Cpk are different, needed to be considered at the same time. 1) Process capability index Cp (the judgment of “gracility” and stability) If the output process randomly variable X tallies the normal distribution, viz. X ~ N (µ, σ). Here µ and σ represent the mean and the standard deviation of X. When a process in the state of statistical control, process capability index Cp = quality standard tolerance/process capability, the formula is: tolerance Cp= processcap acity USL—the standard upper limit of quality characteristics LSL—the standard lower limit of quality characteristics µ and σ can be estimated with sample capacity n. And µ is the mean of the sample. σ is the sample standard deviation of the distribution of process characteristic value. ( ) n ∑ (x σ = _ i − x) 2 i =1 n −1 907 Normally, after calculating the Process Capability Index by the quality characteristic value of the samples, we can analyse the process capability according to the evaluation standard of Cp in table 2. Table 2 Grading Table of the Process Capability Index Grade Index Process capability index Special grade First grade Second grade Third grade Forth grade ( ) Unqualified product rate p % Cp>1.67 1.67≥Cp>1.33 1.33≥Cp>1 1≥Cp>0.67 Cp<0.67 P<0.00006 0.00006≤p<0.006 0.006≤p<0.27 0.27≤p<4.45 p≥4.45 Evaluation Surplus Plenitude Normal Deficiency Serious shortage 2) Process capability index (the judgment of deviation and “aiming degree”) Cpk is used to assess the approaching degree between the actual process and the target mean of the baseline. Cp only depend on σ, as long as 6σ is much smaller than the range of the specification limit, even if the process average µ is far from the target average M. The estimated value of Cp is sizable, which means that the process has a great ability. So, the deviation between the actual average and the target average could lead to the more expense of process adjusting. It means that there are links to be improved, shown in figure 3. Figure 3 The gap between the actual value and the demand value =( ) Cpk is calculated by: Cpk 1-K Cp With the formula for calculating, we can directly determine the process capability according to Cpk by Table 3. We can also put a combination of k and Cp to decide whether a job should be carried out as a core job, or it need to be adjusted, as shown in table 4. Table 3 Evaluation Standard of Cp Index The value of Cpk Cpk<1 Cpk =1 The note about the quality level The process did not meet the minimum standard of the executive ability The process just met the minimum requirements Cpk >1 The process met and exceeded the scheduled minimum standard Table 4 Criteria for Cp when k Exists Process capability index Cp>1.33 Cp>1.33 1<Cp<1.33 1<Cp<1.33 Offset coefficient k 0<k<0.25 0.25<k<0.50 0<k<0.25 0.25<k<0.50 Measures taken No need to adjust the mean Pay attention to the change of the mean Close observation of the mean Take necessary measures to adjust K is the distance between the process average and the mean value of the specification limit. T = USL-LSL 908 M= (USL+LSL)/2 For there is no quality without the coordination of the quality of every link on the chain, including the quality of suppliers, we emphasize on the quality chain in theory. And then in practice, we emphasize on the law, and being engaged with international practice are true reflections of the present situation of quality management. For the managers and quality management departments, this search is very necessary for them to macro-understand, master quality management and suit for the international environment. 4 Quality Management of Data Mining In the era of knowledge economy, other resources are still scarce. But the knowledge is relatively abundant and can be shared. Even the investment of knowledge would lead to "increasing marginal returns", but only on condition that the effective distribution of data, management and utilization. "The economics of the allocation of resources" should be the key indicator of the design of data mining system. Specifically, it is the integration of data mining system and the original system resources. Here, we use a word - "Coupling", which concept is used in many fields. "Coupling" refers to a measure of the interdependence of the two entities. The coupling degree in modular design of computer system measures the degree of interdependence between modules. The smaller the coupling is, the greater the relative independence of modules is. In accordance with the degree of coupling between the Data Mining System (DM) and data warehousing / database (DW / DB), coupling can be divided into the following types of forms: close-coupling, semi-tight coupling, loosely coupling, non-coupling, and so on, specified as follows: 1)Tight coupling Data mining system is viewed as a function component of information system. Data mining query function optimize in accordance with the mining query analysis, data structure, the index model and the query processing methods of DB or DW system. Close-coupling means that DM system is integrated into the DB / DW system smoothly. 2) Loose coupling and semi-tight coupling It means that the DM system is connected to DB / DW, and extracts data from the DB / DW. Some basic original languages of data mining (through analysis of frequently encountered data mining function to determine) are provided by DB / DW. These original languages include sorting, indexing, aggregation, histogram analysis, multi-channel connection, and so on. 3) Non-coupling The Data Mining System (DW) did not make use of any function of database / data warehouse (DB or DW).Its data processing is carried out through a particular source of data such as documents. In this way, the good resources provided by DB / DW are not fully utilized. As can be seen, it is essential that information system achieves some kind of coupling with DB / DW system. On the one hand, from the considerations of quality management, it should increase the consistency, the standardized processing and integration of the capacity of processing capacity, that is, mature of information. On the other hand, considering the economy, it should avoid confusion and waste of resources and allocate resources rationally to enhance the share and integration ability of resources. Therefore, improving coupling between DW and DB / DW system has an important significance in management and economic. Data mining project is inextricably linked with the business intelligence and the data warehouse. In order to strengthen quality management, it is necessary to do the following things: 1)Establish quality management organization Make sure that the work of quality management can get the support from the leadership. 2)Found the quality problem of the data Develop and test data quality management procedures. And design procedures for exception handling. By the test, list common data quality problems, analyse problems and report the related problems to leadership. 3) Strengthen training of the quality management 909 4) Determine the success standard of the quality management project 5) Design the solution process of quality management system 6) Develop the Data Warehouse System 7) Resources coupling To sum up, in the face of enormous social change and development, people's understanding and practice of quality and the quality of management have undergone frequent updates. Juran raised the concept that quality is the "applicability", emphasizing the importance of customer-oriented. In the new century, there emerge some far-reaching new circumstances, requiring adopting corresponding actions. These include the explosive growth of science and technology, human security and health threats, the growing international competition in the quality aspects, unsalable goods sounding the alarm for the company. The tremendously powered cumulative effect makes quality onto the center of the stage, thus triggering a revolution in quality. Replace the narrow quality with a broad sense, establish cooperation relations, and get results in the wider industry and the culture. 5 Conclusion In this paper, we studied the multivariate quality management, such an ambitious campaign is bound to inspire a corresponding response logically, which is the research of quality management systems and knowledge systems. Such a study will have a positive effect on our quality management research and practice. We look forward that this practice will be a new innovation, new tests and new experience, this is a never-ending process. References [1]. Yiping Yang, Hui Ma, Management information system, Economic Science Press[M], December 2006 [2]. Taiwei Chi, The structure design and implementation of data warehouse, Electronics Industry Press, November 2005 [3]. 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