Integrated Cyber Physical Simulation Modelling Environment for Manufacturing 4.0

Lin, W. D.; Low, Yoke Hean; Chong, Yih Tng; Teo, Chee Leong

doi:10.1109/ieem.2018.8607696

Cited by 14 publications

(6 citation statements)

References 6 publications

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“…The exponential development of technology in recent years is highlighted by the concept of Industry 4.0 and respective initiatives in various contexts of the Smart City, Engineering and Construction (SCEC) sectors, such as Building 4.0 [1], Real Estate 4.0 [2], Construction 4.0 [3][4][5][6], Mining 4.0 [7,8], Education 4.0 [9][10][11], and Manufacturing 4.0 [12,13]. The Industry 4.0 concept relies on connecting physical environments with digital ecosystems.…”

Section: Introductionmentioning

confidence: 99%

Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment

2021

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Construction projects and cities account for over 50% of carbon emissions and energy consumption. Industry 4.0 and digital transformation may increase productivity and reduce energy consumption. A digital twin (DT) is a key enabler in implementing Industry 4.0 in the areas of construction and smart cities. It is an emerging technology that connects different objects by utilising the advanced Internet of Things (IoT). As a technology, it is in high demand in various industries, and its literature is growing exponentially. Previous digital modeling practices, the use of data acquisition tools, human–computer–machine interfaces, programmable cities, and infrastructure, as well as Building Information Modeling (BIM), have provided digital data for construction, monitoring, or controlling physical objects. However, a DT is supposed to offer much more than digital representation. Characteristics such as bi-directional data exchange and real-time self-management (e.g., self-awareness or self-optimisation) distinguish a DT from other information modeling systems. The need to develop and implement DT is rising because it could be a core technology in many industrial sectors post-COVID-19. This paper aims to clarify the DT concept and differentiate it from other advanced 3D modeling technologies, digital shadows, and information systems. It also intends to review the state of play in DT development and offer research directions for future investigation. It recommends the development of DT applications that offer rapid and accurate data analysis platforms for real-time decisions, self-operation, and remote supervision requirements post-COVID-19. The discussion in this paper mainly focuses on the Smart City, Engineering and Construction (SCEC) sectors.

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Section: Introductionmentioning

confidence: 99%

Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment

2021

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“…However, dedicated manufacturing 4.0 technologies (Lin et al ., 2018), aided with artificial intelligence (Balamurugan et al ., 2019) gave the opportunity to exploit high data bandwidths in order to optimize information sharing across all the organization, giving the stage to new era manufacturing sequence, in which digital technologies are present seamlessly across the entire development process, namely circular manufacturing (Delpla et al ., 2022), from the early conception of customer-oriented targets (Ahmed et al ., 2021), initial 3D drawing and digital prototyping (Lazorík, 2021), until the ultimate automation and manufacturing with additive manufacturing technologies using Internet of Things (Ashima et al ., 2021; Parmar et al ., 2022) (Figure 3) and quality control (Dutta et al ., 2021; Silva et al ., 2021) solutions of which offer midterm cost-effectiveness (Shivajee et al ., 2019).…”

Section: Introductionmentioning

confidence: 99%

Industrial Design Structure: a straightforward organizational integration of DFSS and QFD in a new industry and market reality

Frizziero

Leon-Cardenas

Galiè

et al. 2023

TQM

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PurposeThe aim of this research is to enlighten the methodology model of Industrial Design Structure (IDeS) that integrates the internal and external customer feedback embodied both in methods of quality function deployment (QFD) and as basis of design for six sigma (DFSS) steps to systematically bring the information across the entire organization, saving overall product development time and resources.Design/methodology/approachThe paper describes the state of the art enlightened to establish the disadvantages and challenges of other methods taken into consideration in the study like QFD and DFSS that, together with the need of companies to react fast to changes they need to straightforwardly implement product development information across all departments, leading to a mass customization infrastructure. Several application trials of this methodology have been cited.FindingsThe IDeS method has established to been able to integrate other well-known methodologies to gather technical specifications starting from voice of customers (VOCs) like QFD that served to canalize the generalist approach of define, measure, analyze, design and verify (DMADV) of DFSS in order to reach into a larger share of the organization and englobe by following the overall product design steps of an industrial project.Research limitations/implicationsThe research approach chosen for this document presents the concept of a methodology ought to operate most internal branches in a company driven by product design requirements and guidelines. Therefore, researchers are encouraged to develop further studies on the IDeS method are required in order to adapt this methodology to specific management tools that would help to ease information gathering for immediate analysis and modification.Practical implicationsThe paper implicates that a need to interchange information systematically across all subdivisions in the organization, as brisk response to VOC reactions is needed to thrive in the market nowadays, leading to a fast product customization scene. However, the industry is heading into adopting an individual customer-centered product conceptualization ought to be driven by design as a key for individualizing an object. Afterward by taking this concept broadly and adopting it would lead to implement a company organization that would be directly affected by the customer's input.Social implicationsThe methodology described aims to enable organizations to portray fast and accurate product prototyping, by exploiting technologies from Industry 4.0.Originality/valueThis concept proposes a method to canalize the implementation of DFSS by using the DMADV approach, whilst assessing the challenges of adaptation and keeping up with cultural pace that impacts the behavior of buying and consumption and moreover implementing a seamless communication within all departments in the organization to share the development progress and change requests by using similar information technology tools. This would imply important savings in resources, whilst delivering quality products to the society.

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“…Implementing the principles of I4.0 into industrial applications is a slow process, mainly due to the generally nonsystematic approach. At present, relevant technologies involve and rely on digitization, robotics, non-optimal data acquisition, virtual reality, IoT, and advanced data processing [ 21 , 22 , 23 , 24 , 25 , 26 , 27 ]; simultaneously, however, application standards remain undeveloped or are lacking completely, and a similar deficiency also affects corporate economy and common initiative in any given field [ 28 , 29 , 30 , 31 , 32 ]. Conversely, these separate technologies help to accelerate the implementation of I4.0 principles and open new opportunities and challenges for technical development; in the given context, such benefits were considered unfeasible 5–7 years ago.…”

Section: Introductionmentioning

confidence: 99%

Automated Design and Integration of Asset Administration Shells in Components of Industry 4.0

Arm

Benešl

Marcoň

et al. 2021

Sensors

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One of the central concepts in the principles of Industry 4.0 relates to the methodology for designing and implementing the digital shell of the manufacturing process components. This concept, the Asset Administration Shell (AAS), embodies a systematically formed, standardized data envelope of a concrete component within Industry 4.0. The paper discusses the AAS in terms of its structure, its components, the sub-models that form a substantial part of the shell’s content, and its communication protocols (Open Platform Communication—Unified Architecture (OPC UA) and MQTT) or SW interfaces enabling vertical and horizontal communication to involve other components and levels of management systems. Using a case study of a virtual assembly line that integrates AASs into the technological process, the authors present a comprehensive analysis centered on forming AASs for individual components. In the given context, the manual AAS creation mode exploiting framework-based automated generation, which forms the AAS via a configuration wizard, is assessed. Another outcome consists of the activation of a virtual assembly line connected to real AASs, a step that allows us verify the properties of the distributed manufacturing management. Moreover, a discrete event system was modeled for the case study, enabling the effective application of the Industry 4.0 solution.

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Integrated Cyber Physical Simulation Modelling Environment for Manufacturing 4.0

Cited by 14 publications

References 6 publications

Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment

Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment

Industrial Design Structure: a straightforward organizational integration of DFSS and QFD in a new industry and market reality

Automated Design and Integration of Asset Administration Shells in Components of Industry 4.0

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