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

Qasim, Iqra; Anwar, Muhammad Waseem; Azam, Farooque; Tufail, Hanny; Butt, Wasi Haider; Zafar, Muhammad Qasim

doi:10.1109/access.2020.2965259

Cited by 23 publications

(14 citation statements)

References 37 publications

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“…Most information systems involve human-computer interaction (HCI). Therefore, HCI has become a key component of any complex system [169], and has become one of the key parts of intelligent manufacturing management [170,171]. According to the vertical framework of the MC-SIOT system, the managers can make real-time decisions through HCI at the management level.…”

Section: Human-computer Interactionmentioning

confidence: 99%

The Architecture of Mass Customization-Social Internet of Things System: Current Research Profile

Dou

Sun

Wu³

et al. 2021

IJGI

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In the era of big data, mass customization (MC) systems are faced with the complexities associated with information explosion and management control. Thus, it has become necessary to integrate the mass customization system and Social Internet of Things, in order to effectively connecting customers with enterprises. We should not only allow customers to participate in MC production throughout the whole process, but also allow enterprises to control all links throughout the whole information system. To gain a better understanding, this paper first describes the architecture of the proposed system from organizational and technological perspectives. Then, based on the nature of the Social Internet of Things, the main technological application of the mass customization–Social Internet of Things (MC–SIOT) system is introduced in detail. On this basis, the key problems faced by the mass customization–Social Internet of Things system are listed. Our findings are as follows: (1) MC–SIOT can realize convenient information queries and clearly understand the user’s intentions; (2) the system can predict the changing relationships among different technical fields and help enterprise R&D personnel to find technical knowledge; and (3) it can interconnect deep learning technology and digital twin technology to better maintain the operational state of the system. However, there exist some challenges relating to data management, knowledge discovery, and human–computer interaction, such as data quality management, few data samples, a lack of dynamic learning, labor consumption, and task scheduling. Therefore, we put forward possible improvements to be assessed, as well as privacy issues and emotional interactions to be further discussed, in future research. Finally, we illustrate the behavior and evolutionary mechanism of this system, both qualitatively and quantitatively. This provides some idea of how to address the current issues pertaining to mass customization systems.

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Section: Human-computer Interactionmentioning

confidence: 99%

The Architecture of Mass Customization-Social Internet of Things System: Current Research Profile

Dou

Sun

Wu³

et al. 2021

IJGI

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“…We practice a Model-to-Text (M2T) transformation approach, using the open source Acceleo tool [16], for the implementation of MODEVES Transformation Engine (MTE). Acceleo is a well-known tool for a seamless execution of transformations in MBSE [29]. Figure 5 shows that the implementation of MTE is accomplished through three main modules: (1) User Interface, (2) Generator and (3) Java Services.…”

Section: A General Architecturementioning

confidence: 99%

A Unified Model-Based Framework for the Simplified Execution of Static and Dynamic Assertion-Based Verification

et al. 2020

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The improved productivity and reduced time-to-market are essential requirements for the development of modern embedded systems and, therefore, the comprehensive as well as timely design verification is critical. Assertion Based Verification (ABV) is a renowned paradigm to timely achieve an optimum test coverage, either through static or dynamic techniques. However, the major limitation with ABV is its inherited low-level implementation complexity. In order to simplify its execution, various Model Based System Engineering approaches provide a higher abstraction layer. Nevertheless, the complete verification requirements, targeting the static as well as dynamic ABV at the same time in a unified framework, are not being addressed. Furthermore, the dynamic verification support is provided through some traditional languages (like C, Verilog) where the advanced ABV features cannot be exploited. Consequently, this article introduces the MODEVES (MOdel-based DEsign Verification for Embedded Systems) framework to simultaneously support the static and dynamic ABV. Particularly, the UML (Unified Modeling Language) and SysML (Systems Modeling Language) diagrams are used to model the structural and behavioral requirements. Moreover, the NLCTL (Natural Language for Computation Tree Logic) is proposed to include the verification requirements for static ABV while the SVOCL (SystemVerilog in Object Constraint Language) is used to represent the dynamic verification constraints. An open source transformation engine is developed to automatically generate the SystemVerilog Register Transfer Level (RTL) code, Timed Automata model, SystemVerilog assertions and Computation Tree Logic (CTL) assertions with minimum transformation losses. The significance of the MODEVES framework is established through several case studies and the quantitative analysis shows an improvement of almost 100% in design productivity, as compared to the conventional low-level implementations.

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“…The validation of MAF is performed in our institution's control lab. An open source Modbus-based Data Acquisition (DA) server is used for the validation of MAF [12]. To develop realistic environment, two Fatek PLCs [38] are utilized where 300 tags are configured to fetch real time values from DA server in order to process alarms accordingly.…”

Section: A Experimental Setupmentioning

confidence: 99%

“…They can acquire, process and log real-time data for particular industrial process. Furthermore, they allow direct and instant monitoring of industrial processes through Human Machine Interface (HMI) [12]. The basic architecture of industrial control systems is shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

“…Data Acquisition (DA) server is a central component of ICS which is responsible to fetch real-time values from multiple PLCs. Subsequently, the fetched values are further processed to display real-time data to operators via HMIs for efficient monitoring and control as The importance of ICS is significantly increased during last decade due to several technological advancements like introduction of Internet of Thing (IoT) [12]. Nowadays, the support for advanced data acquisition and HMI features is mandatory in modern ICS.…”

Section: Introductionmentioning

confidence: 99%

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

Cited by 23 publications

References 37 publications

The Architecture of Mass Customization-Social Internet of Things System: Current Research Profile

The Architecture of Mass Customization-Social Internet of Things System: Current Research Profile

A Unified Model-Based Framework for the Simplified Execution of Static and Dynamic Assertion-Based Verification

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

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