Towards a virtual factory prototype

Jain, Sanjay; Lechevalier, David; Woo, Jiyong; Shin, Seung‐Jun

doi:10.1109/wsc.2015.7408333

Cited by 24 publications

(12 citation statements)

References 13 publications

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“…Sacco, Pedrazzoli, and Terkaj [32] introduced an integrated VF framework concept to synchronize VF with a real factory. Furthermore, the multi-resolution aspect of VF models of real manufacturing systems was presented by Jain et al [33]. VF, as a collaborative design and analysis platform for manufacturing systems, was introduced by Yang et al [34].…”

Section: Virtual Factorymentioning

confidence: 99%

Demonstration and evaluation of a digital twin-based virtual factory

Yildiz

Møller

Bilberg

2021

Int J Adv Manuf Technol

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Smart manufacturing, tailored by the 4th industrial revolution and forces like innovation, competition, and changing demands, lies behind the concurrent evolution (also known as co-evolution) of products, processes and production systems. Manufacturing companies need to adapt to ever-changing environments by simultaneously reforming and regenerating their product, process, and system models as well as goals and strategies to stay competitive. However, the ever-increasing complexity and ever-shortening lifecycles of product, process and system domains challenge manufacturing organization’s conventional approaches to analysing and formalizing models and processes as well as management, maintenance and simulation of product and system life cycles. The digital twin-based virtual factory (VF) concept, as an integrated simulation model of a factory including its subsystems, is promising for supporting manufacturing organizations in adapting to dynamic and complex environments. In this paper, we present the demonstration and evaluation of previously introduced digital twin-based VF concept to support modelling, simulation and evaluation of complex manufacturing systems while employing multi-user collaborative virtual reality (VR) learning/training scenarios. The concept is demonstrated and evaluated using two different wind turbine manufacturing cases, including a wind blade manufacturing plant and a nacelle assembly line. Thirteen industry experts who have diverse backgrounds and expertise were interviewed after their participation in a demonstration. We present the experts’ discussions and arguments to evaluate the DT-based VF concept based on four dimensions, namely, dynamic, open, cognitive, and holistic systems. The semi-structured conversational interview results show that the DT-based VF stands out by having the potential to support concurrent engineering by virtual collaboration. Moreover, DT-based VF is promising for decreasing physical builds and saving time by virtual prototyping (VP).

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Section: Virtual Factorymentioning

confidence: 99%

Demonstration and evaluation of a digital twin-based virtual factory

Yildiz

Møller

Bilberg

2021

Int J Adv Manuf Technol

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“…A few articles address the challenges of standardization and seamless process integration, seamless data aggregation and disaggregation [7], standardization compliance [8], and productservice innovation, product variety, quality standards, support services, and immediacy or order satisfaction [9]. Industrial Automation Systems (IASs) are commonly developed using the de-facto standard IEC 61131 [8].…”

Section: Cps 5 Components Challenge For Manufacturingmentioning

confidence: 99%

A review of CPS 5 components architecture for manufacturing based on standards

Ahmadi

Cherifi

Cheutet

et al. 2017

2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)

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The Cyber-Physical System (CPS) is a concept describing a broad range of complex, multidisciplinary , physically-aware next generation engineered systems that integrate embedded computing technologies (cyber parts) into the physical world. CPS is a broad area of engineering which supports applications across emergency response, air transportation, critical infrastructure, health care and medicine, intelligent transportation, robotic for service, and special smart manufacturing. In particular, CPS is the core technology enabling the transition from Industry 3.0 to Industry 4.0 and is transforming global advanced manufacturing. This paper provides a review of CPS 5 components architecture for manufacturing as well as of CPS components challenges for manufacturing. It then focuses on the standardization challenges and provides a complete review of international standards. From this study we show that there is need for CPS components to be standardized in order to achieve the success of Industry 4.0. A framework of CPS 5 main components for manufacturing based on standards is proposed.

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“…Implementing this approach using AnyLogic, energy consumptions for different parts in their process chain are then compared. Jain et al (2015) also discuss the benefits of combining different agent-based models in a unique DES model of a virtual factory.…”

Section: Towards a Virtual Factory Modelmentioning

confidence: 99%

Simulating a virtual machining model in an agent-based model for advanced analytics

et al. 2017

Self Cite

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Monitoring the performance of manufacturing equipment is critical to ensure the efficiency of manufacturing processes. Machine-monitoring data allows measuring manufacturing equipment efficiency. However, acquiring real and useful machine-monitoring data is expensive and time consuming. An alternative method of getting data is to generate machine-monitoring data using simulation. The simulation data mimic operations and operational failure. In addition, the data can also be used to fill in real data sets with missing values from real-time data collection. The mimicking of real manufacturing systems in computer-based systems is called “virtual manufacturing”. The computer-based systems execute the manufacturing system models that represent real manufacturing systems. In this paper, we introduce a virtual machining model of milling operations. We developed a prototype virtual machining model that represents 3-axis milling operations. This model is a digital mock-up of a real milling machine; it can generate machine-monitoring data from a process plan. The prototype model provides energy consumption data based on physics-based equations. The model uses the standard interfaces of Step-compliant data interface for Numeric Controls (STEP-NC) and MTConnect to represent process plan and machine-monitoring data, respectively. With machine-monitoring data for a given process plan, manufacturing engineers can anticipate the impact of a modification in their actual manufacturing systems. This paper describes also how the virtual machining model is integrated into an agent-based model in a simulation environment. While facilitating the use of the virtual machining model, the agent-based model also contributes to the generation of more complex manufacturing system models, such as a virtual shop-floor model. The paper describes initial building steps towards a shop-floor model. Aggregating the data generated during the execution of a virtual shop-floor model allows one to take advantage of data analytics techniques to predict performance at the shop-floor level.

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Towards a virtual factory prototype

Cited by 24 publications

References 13 publications

Demonstration and evaluation of a digital twin-based virtual factory

Demonstration and evaluation of a digital twin-based virtual factory

A review of CPS 5 components architecture for manufacturing based on standards

Simulating a virtual machining model in an agent-based model for advanced analytics

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