CONSTRUCTION OF A COLLABORATIVE VALUE CHAIN IN CLOUD COMPUTING ENVIRONMENT

CONSTRUCTION OF A COLLABORATIVE VALUE CHAIN

IN CLOUD COMPUTING ENVIRONMENT

Ping Wang, School of Economy and Management, Jiangsu University of Science and

Technology, Zhenjiang Jiangsu China, [email protected]

Zhiying Wang, School of Economy and Management, Jiangsu University of Science

and Technology, Zhenjiang Jiangsu, [email protected]

Juan Yin, School of Economy and Management, Jiangsu University of Science and

Technology, Zhenjiang Jiangsu China, [email protected]

Abstract

In order to solve the problem of matching the demand and service resources in cloud computing environment, the paper puts forward the concept of a collaborative value chain and analyses the collaborative task units and service resource elements. After that, the paper constructs a model of collaborative value chain and describes in detail the process and methods of matching the collaborative value chain tasks and service resources. Based on this model, the paper finally constructs a collaborative manufacturing cloud platform framework for shipbuilding industry and classifies the tasks units and service resources in different stages and describes them respectively.

Keywords: cloud computing environment, collaborative value chain(CVC), Construction of a CVC

1

INTRODUCTION

The development of information technology has spawned a network manufacturing mode, which is a geographically dispersed but closely organized manufacturing system, with different enterprises collaboratively working with each other and responsible for different chains like product design, manufacturing and marketing and etc.

In this way, enterprise resources can be highly shared and allocated so as to maximize value creation(Michael et al. 2000). A network manufacturing mode requires enterprises to find the best partners within the shortest time possible and rapidly form a complete value chain to operate collaboratively and efficiently in order to achieve a win-win situation for each node in the chain.

There are many studies both at home and abroad about the configuration problems within a networked collaborative manufacturing mode. JI(2006) put forward the concept of a collaborative chain oriented at complex parts manufacturing and solves the problem of optimal allocation based on portfolio ant algorithm. LIU and QIAO (2007) proposed a manufacturing resource meta-model and designed a unified manufacturing resource information model framework based on service-oriented architecture and extensible markup language technology, which, solved the problem of integrating manufacturing resources in a multi-application environment. SHEN and FAN (2008) proposed an online service selection by using iterative and incremental validation techniques. Based on the semantic Web and considering the distributive, heterogeneous and service-oriented resources in the cloud designing environment, ZHENG and LUO (2012) designed a collaborative cloud design service platform to achieve integration and sharing of resources and support the integration both internal and external. In addition, studies on networked manufacturing platform, framework and the key technologies are abundant. ZHENG (2012) put forward a method for modeling and optimizing virtual resources suitable for cloud manufacturing and solve the problem by using collaborative multi-objective particle swarm optimization algorithm so as to obtain the optimal virtual manufacturing unit.

The studies above considered only the collaboration in the process of designing or the resource selection in the process of manufacturing, without a complete resource selection covering the entire manufacturing life cycle. Although some proposed methods and processes in resource modeling, they elaborate neither on the task requirements in the processes of designing and manufacturing, nor on the description attributes of service resources. Or they did express service matching mathematically, but didn’t give a detailed account of the whole process. Since the task requirements and service resources are various and numerous in cloud computing environment, this paper is oriented at the whole process of designing and manufacturing and defines the collaborative value chain(CVC) from the perspectives of project management and manufacturing services. In this paper, a task-resource matching model and a strategy optimization model are designed for the collaborative value chain and the two models are applied to the collaborative manufacturing cloud platform in shipbuilding industry.

2

DEFINITION OF A CVC

Driven by customer demand, a collaborative value chain is a chain-like aggregation formed mainly according to product manufacturing. The core enterprise in the value chain usually allocates such task units as designing, simulation, testing, manufacturing and transportation in the product manufacturing process to outer enterprises which are able to provide the above services and can collaborate with each other to achieve the same project.

Due to the complexity in making products, there are two types of value chains, namely, the serial one and the hybrid one. The hybrid value chain is a hybrid link consisting of parallels, selections and circulations. Since the hybrid one can be transformed into a serial one for optimization, the study here will just elaborate on the serial value chain.

From the perspective of project management, CVC is a collection of task units divided along the product life cycle by using project management theories and methods, which can be described as: 1 , 1, 2, 3,..., ; m i i CVC B i m  





In this equation,

B

_irefers to the

i

th collaborative task units in CVC.

From the perspective of manufacturing services, CVC is a manufacturing mode where many enterprises along the product life cycle can collaborate to produce products though they are in different locations, which can be described as:

1 , 1, 2, 3,..., p k k CVC S k p  





In this equation,

S

_kindicates the kth manufacturing service in CVC.

3

CONSTRUCTION OF A CVC

The construction of a CVC is actually a matching between different task units during the formation of the products and a sea of manufacturing services in the cloud computing environment. Some core enterprises in CVC need to make an in-depth analysis of the designing and manufacturing process by using project management methods and make demands and plans. Then, they have to choose collaborative partners to form a CVC and be responsible to monitor and control the whole collaborative process.

Step 1: Defining the collaborative task units

The core enterprises can make a scientific and reasonable division of collaborative task units which are easy to manage and control based on the product life cycle and the knowledge and rules about the industry. The collaborative task units can be described as:

(

,

,

,

,

,

),

1, 2,3,..., ;

1, 2,3,...,

i i i i j i i i

B



BN BO BP BQ BC BT i



m j



n

Here

B

_i indicates the

i

th collaborative task units in CVC, and BN_iis the name of

B

_i.

i

BO is an overall introduction of the content of the collaborative tasks.

BP

_{i j}refers to a

collection of elements in the tasks, and is also a key indicator in the matching of demands and

services. BQ_i is the task load, and BC_iis the upper limit of the task cost, while

BT

_iis the

delivery time for the task.

Step 2: Defining the collaborative service resources

Entities which are qualified to design and manufacture can provide support to the outer entities with their respective resources in forms of services in order to achieve effective integration and collaboration even when the resources are dispersed. Collaborative services can be intelligence-dominated services like designing, simulation and testing, etc., they can also be productive services provided by equipments and hardware. Collaborative services can be described as:

( , , , , , ), 1, 2,3,..., ; 1, 2,3,...,

k k k kl k k k

S  SN SO SP SW SC ST k  p l q

Here

S

_krefers to the kth manufacturing service in CVC and SN_kis the name of it.

k

SO refers to an overall introduction of the content of the manufacturing services.

SP

_klis a

collection of elements in manufacturing services, and is also a key indicator in the matching

of demands and services.

SW

_k refers to service capability, and SC_kis the cost of service

unit, while

ST

_kis the service cycle of the unit.

Step 3: Matching task units and service resources

The forming of a CVC is a process of looking for the best service for each

B

_i, its core being

the matching of

BP

_{i j}and

SP

_kl . In a cloud computing environment, due to the highly

polymerized resources, each

B

_i (the cooperative task) has multiple constituents capable of

providing the same service. The task-service matching process is shown in figure 1. Step 4: Value chain optimization

On the basis of service matching, as well as the strategies of making the lowest cost, the shortest cycle and best quality, a CVC is completed. It might be possible that the recommended routes of the CVC are more than one, so the core enterprises can choose the

best according to their preferences and make some minor adjustments on the recommendations. 1 1 1 ( ) p m m ik i i k i CVC opt S BS    







i

BS

is the collaborative task unit, and

B

i_{is the best matching service found according to the}

CVC building strategies. ①The lowest cost function





1 ( , 1) 1

1 1

min min min ( ) ( , )

m m i i i i i i i i C Cm Ct Cm BS Ct BS BS           _  _ 







Here Cmrefers to the processing costs or the service costs for the entire value chain. Ctis

the transfer cost between two adjacent services.

Cm BS

i

(

i

)

_{is the processing cost or service}

cost of feasible service resource

BS

i_{, which belongs to collaborative task unit}

B

i_.

( , 1)i i ( i, i 1) Ct _ BS BS_

is the transfer cost between feasible service resources in

B

i _and

B

i1_.

If

B

i _and

B

i1 _{are completed by the same service provider, then} Ct( , 1)i i (BS BSi, i1)_is

zero.

②The shortest cycle function





1 ( , 1) 1

1 1

min min min ( ) ( , )

m m i i i i i i i i T Tm Tt Tm BS Tt BS BS           _  _ 







Here Tmrefers to the processing time or service time for the entire value chain. Ttrefers to

the transfer time between two adjacent services. Tm BSi( i)_{is the processing time or service}

time of feasible service resource

BS

i _{, which belongs to collaborative task unit}

B

i_.

( , 1)i i ( i, i 1) Tt _ BS BS_

is the transfer time between feasible service resources in

B

i _and

B

i1_.

If

B

i _and

B

i1 _{are completed by the same service provider, then} Tt( , 1)i i (BS BSi, i1)_is

zero.

③The best quality function

1 min min (1 ( )) m i i i Q Q BS  





Here Q BSi( i)_{refers to the promised quality in processing the feasible service resource} i

BS

_{in collaborative task unit}

B

i_{, and it is indicated by passing rate index.}

The optimization of a value chain can be achieved by combining any two from the above three functions or even all of them based on the features of the manufacturing projects.

extracting collaborative attributesi B Rule(1) 1 i BP 1 k SP Rule(n) ij BP kl SP … … … Rule(3) 3 i BP 3 k SP Rule(2) 2 i BP 2 k SP 1 R R₂ R₃ … R_l 1 2 3 ... l R R R R possible collection 1 i Y 1 i i N i BS extracting service attributes k S 1, 2, 3,..., k p 1 m i i CVC B  



im

Figure 1. Task-service Resource Matching Model

4

APPLICATIONS ON SHIP MANUFACTURING

Due to the complexity of the ship product and its manufacturing process, not only are some special software, equipment and tools needed, but also many professionals are highly demanded. Therefore, the needed services in the ship building process are various in their types, numerous in their number and difficult in selection. In order to solve this problem and improve the efficiency of using the resources, the author of this article and his team intend to build a Shipbuilding Industry Chain Collaborative Manufacture Platform (SICCMP) to cater

to this industry based on a CVC construction model. The following figure 2 is a structure of SICCMP, which is mainly divided into the user access layer, the platform service layer and the data storage layer.

the data storage layer

human resource manufact uring task WBS task manage-ment task release task definition

cooperative task registration

service resources definition service resources manage-ment service resources release

service resource registration

task and service resources matching Value chain formation Optimal policy settings

value chain formation

execution monitoring standard processing bank accessories bank manufacturin g resources bank knowledge and rules bank foundation data bank quality certifica-tion service evalua-tion message manage-ment

platform operation management

security manage-ment tooling resource equip-ment resource design resource simula-tion test resource service provider product design require -ments special equipmen t require-ments manufa cturing require -ments simulat ion test require -ments human resource require-ments service requester

the user access layer

the platform service layer

Figure 2.Cloud platform structure of collaborative ship manufacturing

(1) the user access layer

The customers of SICCMP are mainly two types. One is the core enterprise who will use SICCMP to seek manufacturing resources to complete the product; the other is the service provider who wants to sell the collaborative manufacturing service to outside companies on SICCMP. Users can have access to SICCMP by Internet and use a variety of functions provided by this platform to form a CVC and manufacture the product collaboratively.

(2) the platform service layer

The main function of this layer is to form a CVC and monitor the operation process. Generally, this layer has four functions. 1) cooperative task registration: The product manufacturing life cycle can be divided into different stages like product function designing, process designing, simulation and optimization, manufacturing and testing, etc. If an enterprise is unable to operate some stages or if it is uneconomical to operate them, this enterprise can transmit them to outside enterprises by purchasing or subcontracting. But the enterprise need to define the collaborative task unit very specifically, publish it and monitor

the task implementation process on the platform. 2) service resource registration: After meeting their own production needs, enterprises which have surplus resources or ability can release them in the form of service in order to improve the profit and the efficiency of resource using. This function of the layer includes defining the service resources owned by the enterprise, releasing them and managing them. 3) value chain formation: In response to the released collaborative manufacturing tasks, the system can auto-match tasks and resources, and recommend a set of feasible services and value chains. Enterprises can optimize the model setting by using one single strategy or a combination of strategies to select the best value chain and complete it by negotiating with service providers. After that, enterprises can monitor the whole CVC manufacturing process as well. 4) platform operation management: The platform forms a CVC and manages its operation through qualification, message management, service evaluation and security management.

(3) the data storage layer

The main function of this layer is to provide data storage and management for the operation of the platform, and support the formation and operation of the CVC through accessories bank, standard processing bank, manufacturing resources bank, knowledge and rules bank as well as foundation data bank.

Because of differences of the descriptive elements of task units and service resources between product designing and processing, the expressive elements of the two are strictly defined in the system. In order to make the task-service matching easy, the paper makes the core

elements of

BP

_{i j} and

SP

_{i j}have the same structure because it will improve the matching

efficiency and effectiveness. Next, the paper will take

BP

_{i j}as an example to explain the

collaborative element structure of designing and that of manufacturing respectively in SICCMP.

(1) collaborative element structure of designing

At present, there are various kinds of designing software and simulation software in China’s shipbuilding industry. Since the data formats are different, the collaborative designing is therefore difficult. In addition, during the product designing, some special software is usually needed. Therefore, in designing task collaborative elements, we mainly standardize from such three aspects as enterprise capabilities, design specifications and special software requirements.

( , , , , ; , , ; , )

BP Dq Sf Dt Al Sc Sp Di Do Ss Sv

In this equation, Dqstands for design qualification, Sf for design professional, Dtfor

design type, Al for audit level, Scfor classification societies, Spfor specifications, Di

for data input format, Dofor data output format, Ssfor special software, Svfor software

version.

The accessories of ship products are typically single and small batch machining products, therefore, the defining of collaborative elements of processing is mainly an abstract description of the categories and geometrical characters of the accessories, processing requirements, special equipments and tooling requirements.

( , , ; , , ; P , , , , ; , )

BP P C Ma S W Mf c Mp Mt Mm Sc Eq St

In this equation, P stands for category of the accessories, C for category of the

semi-finished parts, Mafor materials, Sfor size, Wfor weight, Mf for geometric features,

Pcfor production category, Mpfor manufacturing precision, Mtfor manufacturing type,

Mm for manufacturing methods, Sc for classification societies, Eq andSt for special

equipment and special tooling respectively.

5

CONCLUSION

In the cloud computing environment, the effective gathering and highly sharing of resources provide an important foundation condition for the social collaboration, among which a critical point in building a CVC is to select from a sea of similar service resources. In this paper, by giving a definition to CVC, a model is constructed and applied successfully into the collaborative shipbuilding cloud platform. Currently, the platform is still in the development stage. In the next stage, the author of the paper will orient on the application and implementation of the platform and make deeper analysis of the element range of tasks and service resources in designing and manufacturing so as to form a norm for such elements and make a detailed design of optimizing a single strategy or a combination of strategies in the formation of a CVC.

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