Hyun Ahn

Analyzing Risk Dependencies on RFID-driven Global Logistics Processes

In this paper, we try to formally analyze risk dependencies on a global logistics process that is made up of a set of RFID-driven biz-steps2. In enacting a global logistics process, it is very important to control and trace each bizsteps execution as well as to visualize its status. Moreover, for the sake of improving QoS (the quality of services), it ought to be crucial for the system to provide an autonomous error-detection functionality on its running exceptions and very safe self-recovery mechanisms, as well, for the exceptional and risky situations. In resolving the QoS issue, the essential technologies might be RFID and BPM/workflow technologies; workflow is for representing a global logistics process in a natural, and RFID is for implementing each biz-steps application program tagging the logistics information. Also, the essential theory of the self-recovery mechanisms must be on the roll-back mechanism that determines up to where the roll-back operations have to be applied among the previous performed biz-steps on the corresponding global logistics process. As an essential theory of implementing a reasonable roll-back mechanism, the paper particularly formalizes a risk dependency analysis algorithm that is able to produce a set of risk dependency knowledge existing among biz-steps of a RFID-driven global logistics process, and that is eventually used for realizing the self-recovery mechanisms.

Workflow-supported social networks

Technology-supported social networks have been penetrating many aspects of our lives from friendships/blogging sites to working places. The recent BAI (business analytics and business intelligence) systems have also supported the activities of analyzing the social networking issues on employees of companies and their work-sharing relationships, and have used the analyzed issues as a sort of organizational knowledge to deliver quantum improvements in decision-makings and organizational performances. Accordingly this paper focuses on a special type of social networking knowledge called workflow-supported social network that is formed through the deployments and operations of workflow and BPM (business process management) technologies on a workflow-supported organization. In this paper, we formalize a theoretical framework coping with discovery phase and analysis phase, and conceive a series of formalisms and algorithms for representing, discovering, and analyzing the workflow-supported social network. As a theoretical basis, it uses the conceptual methodology of information control nets that used to formally describe workflow procedures and business processes. The theoretical framework is expansively implemented in the name of a systematic framework that is able to automatically discover a workflow-supported social network from an XPDL-based workflow package, construct SocioMatrices from the discovered workflow-supported social network, analyze the SocioMatrices, and visualize the workload centrality measures of all the actors in the corresponding workflow-supported social network. In order to verify the correctnesses of all the discovery algorithms, analysis equations, and the implemented system, we carried out two operational examples. One is for the theoretical framework, the other is for the systematic framework. We applied the theoretical framework to an information control net model of the typical enterprise Hiring workflow procedure, and presented its analyzed results and visualizations. At the same time, by the implemented system we analyzed an XPDL-based workflow package fulfilled by 17 participants, which comprises two imaginary workflow models: Hiring workflow procedure and Presentation workflow procedure consisting of 17 activities and 7 activities, respectively. The analyzed outputs are presented via a series of the captured screen-snapshots produced from the system. Finally, the paper summarizes the implications of the workflow-supported social networking knowledge and how much it is worth in improving decision-makings and organizational performances of workflow-supported organizations and enterprises.

A correspondence analysis framework for workflow-supported performer-activity affiliation networks

The workflow-supported affiliation network is a special type of the workflow-supported social network, and represents affiliated relationships between two different entity types in workflow models. In this paper, we propose a theoretical framework for particularly analyzing the performer-activity correspondence measurements on a workflow-supported affiliation network. The proposed framework formalizes a series of theoretical steps from discovering a workflow-supported performer-activity affiliation network to analyzing the performer-activity association on the discovered affiliation network using correspondence analysis. As an operational example, we apply a typical example of the information control net workflow model to the steps of the procedural framework and show its results of the performer-activity correspondence analysis.

A Gateway-Centered Workflow Rollback-Points Ancestry Model for Sustainable Workflow Enactments

In enacting a workflow process that is made up of stepwise activities and their temporal orderings, it is very important to control and trace each instance’s execution as well as to keep it sustainable. In particular, the sustainability implies that the underlying system should be able to not only provide an error-detection functionality on its running exceptions but also to furnish a very autonomous recovery mechanism to deal with the detected exceptional and risky situations. As an impeccable technique for realizing the sustainability on workflow process enactment services, this paper tries to formalize a workflow risk-recovery concept to be used in implementing autonomous recovery mechanisms of workflow enactment systems, which is named as gateway-centered rollback-points ancestry model. Conclusively, we believe that the proposed model ought be one of those impeccable trials and pioneering contributions to improve and advance the sustainability in workflow process enactment services.

A Theoretical Framework for Closeness Centralization Measurements in a Workflow-Supported Organization

In this paper, we build a theoretical framework for quantitatively measuring and graphically representing the degrees of closeness centralization among performers assigned to enact a workflow procedure. The degree of closeness centralization of a workflow-performer reflects how near the performer is to the other performers in enacting a corresponding workflow model designed for workflow-supported organizational operations. The proposed framework comprises three procedural phases and four functional transformations, such as discovery, analysis, and quantitation phases, which carry out ICN-to-WsoN, WsoN-to-SocioMatrix, SocioMatrix-to-DistanceMatrix, and DistanceMatrix-to-CCV transformations. We develop a series of algorithmic formalisms for the procedural phases and their transformative functionalities, and verify the proposed framework through an operational example. Finally, we expatiate on the functional expansion of the closeness centralization formulas so as for the theoretical framework to handle a group of workflow procedures (or a workflow package) with organization-wide workflow-performers.

A GraphML-based Visualization Framework for Workflow-Performers’ Closeness Centrality Measurements

A hot-issued research topic in the workflow intelligence arena is the emerging topic of “workflow-supported organizational social networks.” These specialized social networks have been proposed to primarily represent the process-driven work-sharing and work-collaborating relationships among the workflow-performers fulfilling a series of workflow-related operations in a workflow-supported organization. We can discover those organizational social networks, and visualize its analysis results as organizational knowledge. In this paper, we are particularly interested in how to visualize the degrees of closeness centralities among workflow-performers by proposing a graphical representation schema based on the Graph Markup Language, which is named to ccWSSN-GraphML. Additionally, we expatiate on the functional expansion of the closeness centralization formulas so as for the visualization framework to handle a group of workflow procedures (or a workflow package) with organizational workflow-performers.

scICN: Scientific information control nets

In this paper, we propose a formal description for representing the scientific workflow model supporting process-driven scientific behaviors in data intensive experiment procedures and large scale computing environments. We try to make a conceptual extension of the information control net methodology so as to be applicable to the scientific workflow models and systems, and dub it scICN (Scientific Information Control Net). Upon the SClCN-based scientific workflow model, we exemplify its application to a pseudo SClCN-based scientific workflow model.

Generating Process Entity Hierarchies from XPDL Process Models.

Business process intelligence enables us to discover a variety of deep insights about business process execution, and it provides a set of useful methods for related decision-making activities. The hierarchical information that this paper focuses on is an important sort of information and it ought to be used in analyzing hierarchical properties of business processes. In this paper, we present a useful hierarchy generator to make it easier to perform analytics of hierarchical properties among business process entities. To this end, we define an abstracted meta-model that represents hierarchical relations among entity types in XPDL process models. According to the relational rules of the meta-model, a process entity hierarchy can be organized, analyzed, and visualized.

Measuring Similarity for Manufacturing Process Models

In manufacturing companies, it is vital to manage their manufacturing processes in order to ensure high quality of products and manufacturing consistency. Because so-called smart factories interconnect machines and acquire processing data, the business process management (BPM) approach can enrich the capability of manufacturing operation management. In this paper, we propose BPM-based similarity measures for manufacturing processes and apply them to the processes of a real factory. In addition to the structural similarity of the existing studies, we suggest a production-related operation similarity. Our contribution is considered on the assumption that a manufacturing company adopts the BPM approach and it operates a variety of manufacturing process models. The similarity measures enable the company to automatically search and reutilize models or parts of models within a repository of manufacturing process models.

Footprint based workflow model for analytical task automation

Generally, analytical tasks target some specific problem that requires engineering expertise to be solved efficiently. However, it is wasteful to use an engineers expertise to address repetitive tasks that are performed iteratively. Therefore, in this paper, we propose a method to automate analytical tasks using the footprint of an approach previously followed by an engineer. Using this method, we can discover and create executable workflow models and use it to automate analytical tasks in manufacturing data analysis.