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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.
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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
（
）
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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;
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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
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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
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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
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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.
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