The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 14, 2014

Filed:

Jan. 15, 2009
Applicants:

Eric W. Cope, Langnau am Albis, CH;

Lea A. Deleris, White Plains, NY (US);

Dominik Etzweiler, Hergiseil, CH;

Jana Koehler, Oberrieden, CH;

Jochen M. Kuester, Zurich, CH;

Bonnie K. Ray, Nyack, NY (US);

Inventors:

Eric W. Cope, Langnau am Albis, CH;

Lea A. Deleris, White Plains, NY (US);

Dominik Etzweiler, Hergiseil, CH;

Jana Koehler, Oberrieden, CH;

Jochen M. Kuester, Zurich, CH;

Bonnie K. Ray, Nyack, NY (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 10/00 (2012.01); G06Q 10/06 (2012.01); G06F 11/07 (2006.01); G06F 9/44 (2006.01); G06Q 40/08 (2012.01);
U.S. Cl.
CPC ...
G06Q 10/0635 (2013.01); G06F 11/079 (2013.01); G06F 8/10 (2013.01); G06Q 10/0633 (2013.01); G06Q 10/067 (2013.01); G06Q 10/06311 (2013.01); G06Q 40/08 (2013.01);
Abstract

A method and computer program product for integrating risk management concepts into a standard business process metamodel by defining a set of metamodel extensions to standard process modeling languages that incorporate risk information directly in the process model. The method includes collecting risk-relevant information for addition to a business process model, and enabling visualizing of a risk-extended business process model. using a notation to express notions as failure modes of resources, root cause events, and sources of execution failure and low job output quality directly in the context of process models. Additionally, the method enables the computation of risk-related impacts on the distribution of process performance measures using a Bayesian network model or a discrete-event simulation model.


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