Towards an extended BPMS prototype: Open challenges of BPM to flexible and robust orchestrate of uncertain processes

Saraeian, Shideh; Shirazi, Babak; Motameni, Homayun

doi:10.1016/j.csi.2017.10.003

Cited by 11 publications

(10 citation statements)

References 14 publications

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“…Out of the 408 included publications, only 23 (5.64 %) reported such applications. The industrial domains include automotive [39,68,79], avionics manufacturing [121,127], packaging [155], production of white goods [9], oil production [71,133], and production of windows and doors [7]. The next section presents our main findings along the four classification dimensions.…”

Section: Umlmentioning

confidence: 96%

Modeling languages in Industry 4.0: an extended systematic mapping study

et al. 2019

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Industry 4.0 integrates Cyber-Physical Systems with the Internet of Things to optimize the complete value-added chain. Successfully applying Industry 4.0 requires the cooperation of various stakeholders from different domains. Domain-specific modeling languages promise to facilitate their involvement through leveraging (domain-specific) models to primary development artifacts. Objective: We aim to assess the use of modeling in Industry 4.0 through the lens of modeling languages in a broad sense. Method: Based on an extensive literature review, we updated our systematic mapping study on modeling languages and modeling techniques used in Industry 4.0 [159] to include publications until February 2018. Overall, the updated study considers 3344 candidate publications that were systematically investigated until 408 relevant publications were identified. Based on these, we developed an updated map of the research landscape on modeling languages and techniques for Industry 4.0. Results: Research on modeling languages in Industry 4.0 focuses on contributing methods to solve the challenges of digital representation and integration. To this end, languages from systems engineering and knowledge representation are applied most often but rarely combined. There also is a gap between the communities researching and applying modeling languages for In

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Section: Umlmentioning

confidence: 96%

Modeling languages in Industry 4.0: an extended systematic mapping study

et al. 2019

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“…There is a lack of robust approaches for BPI implementation [58], [59]. Taguchi provides a robust approach [60] by identifying controllable factors (vision, skills, resources, incentives and action plan) that minimize the effect of the uncontrollable (noise) factors.…”

Section: Identification Of Research Gapmentioning

confidence: 99%

Identifying Control Factors for Business Process Improvement in Telecom Sector Using Taguchi Approach

Ibrahim¹,

Hanif

Ahsan

2019

IEEE Access

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Business Process Improvement (BPI) projects open avenues of success for organizations in this highly competitive era. However, most of these projects are not completed due to various reasons identified in past studies making it an area of active research. Using the Taguchi method, this paper identifies industry relevant factors that are most critical to success of a BPI Project in the Telecom sector. Data collected from business process managers and teams was used in evaluating the factors that significantly affect BPI project success through Taguchi Method. The experimental results and findings enable the managers of Telecom organizations to conduct successful BPI projects by guiding them about the factors that are determined to be highly critical to success. Vision, skills, resources, incentives and action plan were determined as critical factors that lead the BPI project towards success. The primary contribution of this research is the proposed methodology and the design of experiment based on the Taguchi Method to determine levels of critical factors in the services sector where this has limited application as compared to the manufacturing industry. The practical implications of this research relate to providing concise directions to ensure success of BPI Projects in the Telecom sector prior to execution of the project. A significant contribution of the research is its practicability in implementation across different industries. INDEX TERMS Business process improvement (BPI), critical success factors (CSFs), change accelerated process (CAP), Taguchi, robust design, orthogonal array (OA).

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Section: Introductionmentioning

confidence: 99%

“…BPMS, as an information system, can examine business processes to guarantee activities and tasks have pro table execution [7]. The current uncertain Business Process Management System (uBPMS) architecture [7,8] does not consider the business process orchestration. This paper aims to achieve an extension of uBPMS architecture [7,8] with a business process orchestration feature to make a response in real time and satisfy the demands, uncertainty conditions, and so on in a smart factory.…”

Section: Introductionmentioning

confidence: 99%

The role of bi-level uncertain architecture inward smart manufacturing: Process orchestration

Saraeian

Shirazi

2023

Scientia Iranica

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Smart manufacturing in the context of a smart factory is allowed through di erent uncertain processes, which creates signi cant challenges. In this case, smart manufacturing should be applied reliably, interoperably, and consistently. Thus, it faces the requirement of orchestrating services provided by uncertain processes to satisfy the challenges. These uncertain processes are commonly managed by an uncertain Business Process Management System (uBPMS), which is speci cally designed to address unknown conditions. The current uBPMS architecture does not consider business process orchestration, and the objective of this paper is to achieve an extension of uBPMS architecture with a business process orchestration feature to make a response in real time and satisfy the uncertainty conditions in a smart factory. The proposed extension can perform autonomous orchestration of business processes inward traditional uBPMS architecture based on desired values of di erent objectives optimization. This new architecture operates based on a robust bi-level optimization approach. The Rousselot smart factory in Belgium as a simulated case study was studied. The results show the robustness of the new architecture for process orchestration design in this case. Also, uncertain business process management based on the process orchestration feature presents e ciency and accuracy improvement in smart manufacturing systems.

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Towards an extended BPMS prototype: Open challenges of BPM to flexible and robust orchestrate of uncertain processes

Cited by 11 publications

References 14 publications

Modeling languages in Industry 4.0: an extended systematic mapping study

Modeling languages in Industry 4.0: an extended systematic mapping study

Identifying Control Factors for Business Process Improvement in Telecom Sector Using Taguchi Approach

The role of bi-level uncertain architecture inward smart manufacturing: Process orchestration

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