UMLPACE for Modeling and Verification of Complex Business Requirements in Event-Driven Process Chain (EPC)

Amjad, Anam; Azam, Farooque; Anwar, Muhammad Waseem; Butt, Wasi Haider; Rashid, Muhammad; Naeem, Aamir

doi:10.1109/access.2018.2883610

Cited by 9 publications

(7 citation statements)

References 38 publications

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“…There are other imperative model besides BPMN, i.e. Petri Nets [9], Yet Another Workflow Language (YAWL) [10], and Event-Driven Process Chains (EPC) [11]. The second representation, declarative model [12], uses rules to declare the operators of parallel relationships.…”

Section: Introductionmentioning

confidence: 99%

Novel Parallel Business Process Similarity Methods Based on Weighted-Tree Declarative Pattern Models

Wahyuni¹,

Sungkono²,

Sarno³

2019

IJIES

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Existing methods, such as Graph Edit Distance (GED) and Cosine measure, still have drawback in obtaining similarity of parallel relationships by neglecting the control-flow patterns, i.e. AND, OR, and XOR. Since AND > OR > XOR, the similarity value of AND versus OR is greater than XOR versus OR and AND versus XOR. This paper proposes two new similarity methods, Tree Declarative Pattern Edit Distance (TPED) and Cosine-Tree Declarative Pattern (Cosine-TDP). They provides value to the control-flow pattern so the value of similarity can be seen more differently. The new methods utilize tree model of the declarative pattern. The results show that the proposed methods are better at differentiating parallel relationships than the existing methods, GED and Cosine measure. In obtaining AND versus OR, XOR versus OR, and AND versus XOR, TPED obtained 0.821, 0.811, and 0.78 while Consine-TDP obtained 0.834, 0.826, and 0.693. Meanwhile, GED obtained 1 for all parallel relationships whereas Cosine measure obtained 0.02, 0.08, and 0.04.

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Section: Introductionmentioning

confidence: 99%

Novel Parallel Business Process Similarity Methods Based on Weighted-Tree Declarative Pattern Models

Wahyuni¹,

Sungkono²,

Sarno³

2019

IJIES

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“…UML Profile for Mobile HMI (UMLPMH), provides a generic extension mechanism that allows to extend and customize meta-model (i.e. UML) using stereotypes [43] by introducing domain specific concepts of mobile HMI for industrial control systems. Stereotype is a profile class defines, how an existing metaclass can be extended as a part of profile [32].…”

Section: A Uml Profile For Mobile Hmi (Umlpmh)mentioning

confidence: 99%

A Model-Driven Mobile HMI Framework (MMHF) for Industrial Control Systems

et al. 2020

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With the advent of software technologies, over a period of time, the Industrial Control Systems (ICSs) have grown exponentially. Whereas, almost all ICSs comprise Human Machine Interfaces (HMIs), which are the key component for monitoring and controlling complex industrial systems. For decades, traditional HMIs with simple User Interfaces (UIs) remained operational to minimize the complexities and resulting operational costs. However, due to the emergence of smartphone technologies, the perception about user interfaces has been transformed significantly and users now demand same sort of experience with industrial HMIs, as well. There are few industrial solutions, like, ICONICS GraphWorX to support the development of mobile HMI screens. However, such proprietary solutions are quite expensive. Furthermore, the underlying development approaches and source codes are not accessible in public domain. On the other hand, the state-of-the-art approaches for the development of native mobile HMI screens are hard to find in the literature. Consequently, there is dire need of a cost-effective, easy to use, open source framework for the development of native mobile HMI screens. In order to achieve this goal, here we propose, a Model-driven Mobile HMI Framework (MMHF). MMHF comprises, a Unified Modeling Language (UML) Profile for Mobile HMI (UMLPMH) for modeling of HMI screens. MMHF also includes, an open source transformation engine and a Model Driven Mobile-based HMI Code Generator (MDMHCG) to automatically transform UMLPMH models into target native mobile HMI implementations. Consequently, MMHF enables simpler way to design the HMI screens using UMLPMH and generates native Mobile HMI Screen implementations automatically using MDMHCG. The empirical evidence of MMHF is demonstrated through three (3) benchmark case studies, which prove that the MMHF is a feasible, cost effective and scalable solution to develop native HMI screens for wide-ranging ICSs. INDEX TERMS Human machine interface, mobile HMI, model driven engineering, unified modeling language, industrial control system, industry automation, Internet of Things (IoT).

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“…UML is a general-purpose modeling language. UML can be extended through Profile mechanism to make UML a domain specific modeling language (DSML) [46]. UML profile is like a package in UML and uses same notation as well with just the addition of "Profile" guillemet that precedes the name of a profile.…”

Section: B Alarm Profile For Industrial Control Systems (Apics)mentioning

confidence: 99%

A Model-Driven Alarms Framework (MAF) With Mobile Clients Support for Wide-Ranging Industrial Control Systems

et al. 2020

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An efficient and robust alarms management is an extremely desirable feature to prevent critical failures in modern Industrial Control Systems. Generally, alarm systems are categorized into two major components; i.e., Alarm Server and Alarm Client. Alarm server is responsible to process alarms on real time values, while alarm clients display the generated alarms. With the advent of modern technologies, like, Internet of Thing (IoT), the need for mobile alarm clients has significantly been increased, as alarms need to be displayed on different gadgets instead of traditional big screens. Owing to significance of alarms in the industry, several state-of-the-art approaches have been introduced, suggesting various improvements. However, such approaches are only meant for specific industry and cannot be applied across-the-board. Furthermore, full support for mobile clients is not available. On the other hand, certain industrial software products like, SIMATIC WinCC, Genesis64 provide complete alarm solution including mobile client features, as well. However, such solutions are proprietary with higher costs, i.e., pay per tag model. Considering such limitations, this article proposes a novel Model-driven Alarms Framework (MAF) with mobile clients (Android and iOS) support. Particularly, MAF comprises an Alarm Profile for Industrial Control Systems (APICS) for the modeling of server, mobile clients and configuration requirements of alarms with remarkable simplicity. Furthermore, a complete open source Alarms Profile Transformation Engine (APTE) has been implemented to automatically generate alarm server (Kotlin), native Android (Kotlin) and iOS (Swift) alarm clients from APICS-compliant models. The feasibility of proposed framework is demonstrated through two case studies (flour mill and home automation). The results prove that MAF not only provides complete alarm server solution to generate bulk of alarms simultaneously, but also supports android and iOS alarm clients for efficient visualization. Besides that, MAF is easy to use, cost-effective and can be applied in wide-ranging industrial applications.

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UMLPACE for Modeling and Verification of Complex Business Requirements in Event-Driven Process Chain (EPC)

Cited by 9 publications

References 38 publications

Novel Parallel Business Process Similarity Methods Based on Weighted-Tree Declarative Pattern Models

Novel Parallel Business Process Similarity Methods Based on Weighted-Tree Declarative Pattern Models

A Model-Driven Mobile HMI Framework (MMHF) for Industrial Control Systems

A Model-Driven Alarms Framework (MAF) With Mobile Clients Support for Wide-Ranging Industrial Control Systems

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