Risk Analysis and Evaluation of Modular Production Network

Peng Benhong, Zong Qi(Corresponding author) School of Economics and Management, Nanchang HangKong University, NanChang, 330063, China

pbh21@163.com

Abstract—The complexity of modular production makes

modular production network full of risks. The five special

risks among modular production network are presented in the

paper. According to its uncertainty and fuzzy characters,

Fuzzy AHP is used to evaluate the risks of modular production

network. An example is applied to explain its operational. This

method combines the advantages of AHP and fuzzy evaluation

method with strong operational.

Keywords: Modular Production Network; Fuzzy AHP;

Network Risk

I. MODULAR PRODUCTION NETWORK 1 The emergence of modular production networks

makes multiple enterprises engaged in production and management originally performed by only one enterprise. Therefore the boundaries of vertically integrated companies which comprise the whole process of production and operation activities are broken[1]. Although the integration is conducive to achieving scale economy and scope economy, yet it’s unable to adapt to the flexibility and response capacity Of the knowledge economy times. The modular production mode in era of knowledge economy needs more effective integration and teamwork within the enterprise's internal, between the enterprises and enterprises and suppliers, enterprises and partners, enterprises and customers. Therefore, enterprise organization form compatible with modular production mode has undergone change, and the module production networks appears.

Modular production network is an open network organization which makes the modules production and assembly emterprises connected together based on This work is supported by Grant for the National Nature Science Foundation of China( 70962008)

relationship, taking the product’s modularization as premise, it is a new organization form adapting to the modular technology. Modular production network is not subject to geographical limitation, which can be either a geographic location of the mutual attractive place for the industry, or be cross-regional, transnational organization network. The connotation of modular production network indicates that it’s a reflection of inter-organizational relationships on the dependent elements, contact elements, and encouraging compatibility between the organizational elements of governance model[2].

II.THE SPECIFIC RISK OF MODULAR PRODUCTION NETWORK

As an open production system, modular production networks, on the one hand, carry out the modularization of departments or branch offices around the product or function’s modularization within the enterprise, break product value chain into separate nodes, just as modular process; On the other hand, outside the enterprise, through outsourcing, OEM and other activities, and business alliances, implementation of "organization modularization" process outside of enterprise. The risks are from the modular processes and "organizational modularization" [3]. The risks include:

A. Intellectual property risk

In modular production networks, systems integrators are often dominant firms or core business, outsourcing process in knowledge management become increasingly important. Leakage of knowledge on the core business would have a serious negative impact: on the one hand module supplier may develop its own products to compete with the dominant firms using the knowledge gained, on the other hand, if the module supplier that provide services for

2010 International Conference on Intelligent Computation Technology and Automation

978-0-7695-4077-1/10 $26.00 © 2010 IEEE

DOI 10.1109/ICICTA.2010.119

210

several leading companies may offer certain key business information to its competitors. Thus, intellectual property protection in modular production networks has become important factors.

B. Compatibility Risk

Compatibility is the most critical parameter in modular production networks, which means technical level of merge of different module, bringing the co-existence or joint use of module without conflict. The module is a system composed by a set of interconnected nodes and a number of interwoven branches. The connection between nodes can be a physical connection or invisible virtual connection[4]. Eg, in order to ensure that the module can play correctly, the drive module suppliers must comply with the general requirements of personal computers in data transmission of technical procedures, the size of the hardware specifications, interface standards and so on. Therefore, compatibility of interface between different value modules is an important issue of modular production networks.

C. Network risk

Modular production mode needs more effective Integration within the enterprise, enterprise and suppliers, enterprise and partners, enterprises and customers. Modularization has spurred the production organization transformation and module production networks occurred. In the enterprise's commercial ecosystem, with the value chain elongation, decomposition and networking, an enterprise's internal network and external network docking into an open network, value creation, exchange and sharing distribution across the network[5]. Network system basic variables (activities, actors and resources) are interdependent, and thus constitute a complex network of relationships to form a network effects or network externalities. In the development process of modular production networks, the network effect is a "double-edged sword", and can generate two distinct roles to the evolution of value module[6]. On one hand, network effects can generate a virtuous cycle to promote the development and upgrading of the value module. On the other hand, network effects can also generate a vicious circle, resulting in

network failure, or serious negative feedback effect of the network.

D. Information Risk

The interface standard and information enclosure mode of modular production network is a system of mutual promotion and common evolution maintenance. In the process of module standardization, system information of module design is public, but some special information keep secret mutually, development or improvement of each module need not coordination of other module at design contents. Module development corpus follows the general design rule. The information dissymmetry between module supplier and system integration enterprise form information risk, Harold Demsetz thought that the information cost occupy an important position in the bargain cost theories, and more fundamental[7].

E. Property Special Risk

With the increment of outsource network node, System integration enterprise manages module suppliers more difficult. At present, system integration enterprise tend to reduce the number of module suppliers. Module supply and demand parties invest large at human resource, process rule and fixed assets, this kind of special investment once occurred, it is very difficult to replace cooperation colleague. Thus property special risk formed.

In module production network, close of the correlation between system integration enterprise and module supplier lowered bargain cost, which gradually change into a closed system structure, making the whole module system can't carry on an information, energy exchange quickly with the external world, strain capacity to environment decrease continuously and form locked up effect.

III.THE F-AHP OF RISK EVALUATION OF MODULAR

PRODUCTION NETWORK

According to the information data for control dissimilarity, there are four kinds of risk valuation methods, just as assurance type, risk type, indetermination type, and Bayes probablity. The risk of modular production network belongs to indetermination type, whose appearance and

211

appearance occurrence probablity can't be assured completely. In fact, the indetermination may be converted to risk problem through information gained, such as fuzzy analytic hierarchy process (Fuzzy-AHP, F-AHP). AHP only consider two kinds of probabyly extreme circumstance when importance comparision within project [8], which doesn’t consider the indistinct of person judgment, while F-AHP combine their advantages.

Definition 1[9] Supposed that judgement matrix A=（aij）

n*n , among, aij=( lij，mij，uij)，aji=( lji，mji，uji). If lij+ uji =mij +mji

= uij +lji=1，uij≥mij ≥lij≥0，i，j�N, then we may call A as

triangle fuzzy number mutually supplement judgement matrix.

Definition 2 A1=( l1，m1 ，u1) and A2=( l2，m2，u2) are

both triangle fuzzy numbers, then probability of A1≥A2 is:

2 1 2 1

1 1 2 2 1 1 2 2

1 1max{1 max[ ,0} max{1 max[ ,0}2 2

m l u mVm l m l u m u m

− −= − + −− + − − + −

。

(1) The risk method of F-AHP is divided into four

steps:modeling of risk factor analysis structure; Construction and consistency check of fuzzy risk judgment matrix; The ordering of the fuzzy risk judgment matrix; The total ordering of risk factor hierarchy.

IV. INSTANCE ANALYSIS

Aviation engine is a kind of typical model of complicate product with high technique, strong innovation, large funding, and long developing and production cycle. Among the process of modular production, the risk factors pile up one after another, and influence mutually, if some link doesn’t consider completely, serious economy loss may be induced. Therefore, the risks among production need complete and accurate evaluation. At present, traditional probablity statistics method and expert judgment method usually can't make overall and accurate evaluation to aviation item numerous risk factor. This paper make use of F-AHP valuation method to analyze and research risk

valuation, realize importance ordering of risk factors. Now making some aviation engine enterprise as example, analyzed the real process based on F-AHP risk valuation method.

At first risk hierarchy structure model of modular production network of aviation engine are set up(figure 1) .

Then, according to the risk analystic hierarchy structure model of production network of the Dawn aviation engine as figure 1 shown, we can establish the original judgment matrix of all layers. Through investigation and consultation to concerned personnel and expert, the original judgment matrix was established;(table I, table II)

Secondly, relative power vector of each layer are calculated arrcoding to the original judgment matrix of table II and table III, and the results are attached in table II and table III.

At last, from the relative power vector of above layer, we may calculate the ordering power vector to the lowest layer, and the calculation result as follows to the target layer and standard layer:

WA=（0.122，0.041，0.197，0.066，0.182，0.109，0.036，0.052，0.155，0.02，0.02);

WB1=（0.094，0.031，0.125，0.042，0.209，0.125，0.042，0.073，0.220，0.02，0.02);

WB2=（0.15，0.05，0.27，0.09，0.157，0.093，0.031，0.09，0.03，0.02，0.02).

According to the calculation result of above ordering power vector, we can gain bj=.(0.45, 0.16, 0.18, 0.16, 0.05). So we can carry on risk management in the production network of aviation engine, establish risk counterplan, guard against the high level risk as emphasis.

V. CONCLUSION

Combining triangle fuzzy number and analysis hierarchy method, a kind of risk valuation method was put forward according to Fuzzy AHP, which carrys on hierarchy analysis of risk factors according to AHP, describes expert judgment information through triangle fuzzy number, with the help of Fuzzy risk judgment matrix to realize improtantce ordering based on risk occurrence probablity, risk loss and comprehensive consideration of

212

risk occurrence probablity and risk loss. With the method to evaluate project risk, it is enough that only personnel and

expert concerned give comparison judgment information of risk factors, and his kind of method has strong operational.

VI. FIGURES AND TABLES

TABLE I. A-B Fuzzy risk judgment matrix

A B1 B2 P

B1

B2

(0.5，0.5，0.5)

(0.5，0.5，0.5)

(05，.05，0.5)

(0.5，0.5，0.5)

0.500

0.500

TABLE II. B—C1 Fuzzyrisk judgment matrix(B—C1) B1 C1 C2 C3 C4 C5 P C1 C2 C3 C4 C5

(0．6，0．7，0．8) (0．5，0．5，0．5) (0．7，0．8，0．8) (0．7，0．8，0．8) (0．3，0．3，0．5)

(0．7，0．7，0．8) (0．2，0．2，0．2) (0．5，0．5，0．5) (0．6，0．6，0．7) (0．4，0．4，0．5)

(0．5，0．5，0．5) (0．2，0．3，0．4) (0．2，0．3，0．3) (0．2，0．3，0．4) (0．2，0．3，0．3)

(0．6，0．7，0．8) (0．2，0．2，0．3) (0．3，0．4，0．4) (0．5，0．5，0．5) (0．1，0．2，0．2)

(0．7，0．8，0．8) (0．5，0．6，0．7) (0．5，0．6，0．6) (0．8，0．8，0．9) (0．5，0．5，0．5)

0．375 0．125 0．167 0．293 0．040

TABLE III. B—C2 Fuzzyrisk judgment matrix(B—C2)

B1 C1 C2 C3 C4 C5 P C1 C2 C3 C4 C5

(0．6，0．7，0．7) (0．5，0．5，0．5) (0．5，0．7，0．7) (0．3，0．3，0．4) (0．3，0．3，0．4

(0．2，0．3，0．4) (0．3，0．3，0．5) (0．5，0．5，0．5) (0．2，0．2，0．3) (0．1，0．1，0．2)

(0．5，0．5，0．5) (0．3，0．3，0．4) (0．6，0．7，0．8) (0．3，0．3，0．4) (0．2，0．2，0．3)

(0．6，0．7，0．7) (0．6，0．7，0．7) (0．7，0．8，0．8) (0．5，0．5，0．5) (0．3，0．3，0．4)

(0．7，0．8，0．8) (0．6，0．6，0．7) (0．8，0．9，0．9) (0．6，0．7，0．7) (0．5，0．5，0．5)

0．280 0．200 0．360 0．120 0．040

REFERENCE

[1] STARR MK. Modular production to a new concept[ J ]. Harvard Business Review, 1965, 43: 131—145 [2] XuHong-lin. Research on Modular Organization[M]. ChenDou: South and West Financial and Economic Publishing House，oct, 2006 [3] ShunXiao-feng .Research on Modular Production Network[J]. China Industry Economy, 2005(9). [4] GuoLan，ZhangXiang-jian，XuJin. the micro-Structure and Risk Characteristic: Based on the Analysis on Industry Cluster[J], 2008, 29(5): 56- 57 [5] LiHai-jian, YuanLei. Research on Profit Conversion based on Value Chain Level[J]. China Industrial Economy, 2005 (6) [6]CaiLing, YangYan-zhu, WuJie-bing. Research on the Risk of Enterprise Cluster: Based on the View of Network [J]. China Industrial Economy, 2003 (4)

[7] ZhangJian-xiang, WangDong-jing. Analysis on the Risk Structure of high-new Technology Industry[J]. ShangHai Economy Research, 2007, (6) :22-25 [8]Xhu Shu-bo. Decision Method-Principle of Hierarchy Analysis [M]. TianJin: TianJing University Publishing House, 1988. [9]XuZhe-shun, the Ordering Method of Triangle Fuzzy Number Complementation Judgment Matrix[J], Fuzzy System and Mathematics, 2002

Ordering of risk fators A

Risk occurrence loss of B1 Risk occurrence loss of B2

Intellectual property risk C1

Networkrisk C3

Informationrisk C4

Assert special risk C5

Compatibility Risk C2

Figure 1. The risk analystic hierarchy structure model of production network of the Dawn aviation engine

213