Interoperative end-user process modelling for process collaborative manufacturing

This source preferred by Paul De Vrieze, Sherry Jeary, Lai Xu and Keith Phalp

Authors: Xu, L., de Vrieze, P., Phalp, K., Jeary, S. and Liang, P.

http://www.scopus.com/inward/record.url?eid=2-s2.0-84887442579&partnerID=40&md5=490e2e8568b46367afa56c6c8aab8f34

Journal: International Journal of Computer Integrated Manufacturing

Volume: 26

Pages: 990-1002

DOI: 10.1080/0951192X.2012.685107

This source preferred by Paul De Vrieze, Sherry Jeary, Lai Xu and Keith Phalp

Authors: Xu, L., de Vrieze, P.T., Phalp, K.T., Jeary, S. and Liang, P.

Journal: International Journal of Computer Integrated Manufacturing

Pages: 1-13

ISSN: 0951-192X

As business environments change rapidly the ability to quickly set up a collaborative automated business processes is desirable. Collaborative business processes are increasingly driven by business agility, adaptability, and flexibility, particularly in a modern manufacturing enterprise environment. Traditionally collaborative business processes are used among big organisations. Many of collaborative business process systems are designed for a long term use with central control. It is a great challenge for enterprises to adapt processes to the today’s business pace. Today's enterprise users demands many situational collaborative business process applications which handle business needs within a short period and which normally do not need to support too many users. The traditional centrally controlled systems are not designed for such situational applications. In this paper, we explore how business process mashups can be used for manufacturing enterprise collaboration. We highlight the modelling of end users process collaboration from both a control flow and a data flow perspective. Based on our analyses, an end user process modelling approach is proposed for process enterprise mashup applications. Our approach, illustrated by reference to an example pharmaceutical collaborative manufacturing case, will support collaboration among users with different levels of modelling skills and expertise in a pharmaceutical manufacturing enterprise environment.

This data was imported from DBLP:

Authors: Xu, L., Vrieze, P.D., Phalp, K., Jeary, S. and Liang, P.

Journal: Int. J. Computer Integrated Manufacturing

Volume: 26

Pages: 990-1002

This data was imported from Scopus:

Authors: Xu, L., De Vrieze, P., Phalp, K., Jeary, S. and Liang, P.

Journal: International Journal of Computer Integrated Manufacturing

Volume: 26

Issue: 11

Pages: 990-1002

eISSN: 1362-3052

ISSN: 0951-192X

DOI: 10.1080/0951192X.2012.685107

As business environments change rapidly, the ability to quickly set up a collaborative automated business processes is desirable. Collaborative business processes are increasingly driven by business agility, adaptability and flexibility, particularly in a modern manufacturing enterprise environment. Traditionally, collaborative business processes are used among big organisations. Many of collaborative business process systems are designed for a long-term use with central control. It is a great challenge for enterprises to adapt processes to the today's business pace. Today's enterprise users demand many situational collaborative business process applications which handle business needs within a short period and which normally do not need to support too many users. The traditional centrally controlled systems are not designed for such situational applications. In this paper, we explore how business process mashups can be used for manufacturing enterprise collaboration. We highlight the modelling of end-users process collaboration from both a control flow and a data flow perspective. Based on our analyses, an end-user process modelling approach is proposed for process enterprise mashup applications. Our approach, illustrated by reference to an example pharmaceutical collaborative manufacturing case, will support collaboration among users with different levels of modelling skills and expertise in a pharmaceutical manufacturing enterprise environment. © 2013 Copyright Taylor and Francis Group, LLC.

This data was imported from Web of Science (Lite):

Authors: Xu, L., de Vrieze, P., Phalp, K., Jeary, S. and Liang, P.

Journal: INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING

Volume: 26

Issue: 11

Pages: 990-1002

eISSN: 1362-3052

ISSN: 0951-192X

DOI: 10.1080/0951192X.2012.685107

The data on this page was last updated at 04:51 on July 17, 2018.