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Case Study

Adaptive Scheduling Digital Twin

Project challenges

Dynamic changes are unavoidable in real world manufacturing scenarios. Key to success is an organisation's ability to quickly respond and adapt to new situations.

Business challenge

  • Digital Transformation

Sector

  • Aerospace

Technology or capability

  • Digital Manufacturing

  • Simulation & Modelling

  • Industrial Transformation

A factory digital twin is a virtual representation of the physical manufacturing facility, processes, and systems within the digital realm. 

This system-of-systems technology creates a synchronised mirror image of the real-world factory. The concept of a factory digital twin involves synchronising the physical and digital aspects of factory systems to enhance decision-making, efficiency, and overall performance. Factory digital twins enable real-time monitoring, adaptive operations management, and intelligent control across manufacturing operations, as well as logistics and the factory supply chain. These bring a wide range of benefits including flexibility and adaptability, optimised operations, data-driven decision making, predictive maintenance, and continuous improvement. 

The research work to develop a proof-of-concept for the adaptive scheduling digital twin has been undertaken as part of the AeroMC - Aerospace Manufacturing Capability for Electrical Machines project. The AeroMC project is led by Safran UK Ltd. and partners with WMG and MTC, to investigate aerospace manufacturing capability for electric machines. Based at Pitstone in the UK, Safran’s ‘Electrical Power’ business is Safran’s global centre of expertise for manufacturing conventional technology electrical generation, controls and power systems. The AeroMC project looks at new technologies for hybrid propulsion technologies on aircrafts; including electrical Vertical Take-Off and Landing (eVTOL), electrical Conventional Take-Off and Landing (eCTOL), electric Short Take-Off and Landing (eSTOL) – and establishes a UK facility as global centre of manufacturing expertise for these new technologies.

The Challenge
  • Dynamic changes are unavoidable in real world manufacturing scenarios. 
  • There are many sources of changes across manufacturing organisations; common examples include: rush orders, equipment failure, cancelled orders, labour shortage, and late deliveries supplies.
  • Collect up-to-date and reliable information on the latest situation to make optimal decisions to minimise overall impact. 
  • Key to success is an organisation's ability to quickly respond and adapt to new situations.
MTC's Solution
  • Automatic detections of changes from live data
  • Connected production simulation to predict future impact across factory performance indicators.
  • Computational intelligence algorithms to identify optimal response to changes and minimise impact.
  • Digital integration platform to embed digital twin across manufacturing operation management systems, such as EPR, MES, etc.
  • Developed using MTC member's software, include Siemens Tecnomatrix Plant Simulation, Siemens Simcentre HEEDS, and FICO Xpress, amongst others.

This work is a key example of MTC’s digital engineering ability to mature and refine the latest technological innovations, and support de-risking adoption for aerospace manufacturing, accelerating digital transformation.

Paulino Rocher, Technology Manager, MTC

The Outcome
  • End-to-end digital twin proof-of-concept demonstrator.
  • Demonstration of a range of scenarios representing real-world dynamic changes in aerospace manufacturing.
  • Solution architecture designed for digital twin's system-of-systems integration.
  • Data flows mapped and linked to suitable middleware components.
  • Activity diagrams specifying functional requirements for development and implementation.
  • User experience to embed digital twin across digital manufacturing operation management systems, such as ERP, MES, CMMS, etc.
Benefits to the Client
  • Proof of concept demonstration of digital twin solution with integrated digital technologies.
  • Digital twin solution design that works for the client’s organisation, tailored to specific needs and priorities.
  • Tool to assess business case to de-risk and justify digital twin investment as well as identification of operating model opportunities.
  • Knowledge transfer on digital twin technologies and integrations to become intelligent customer for further development and adoption.
  • Digital twin ontology as a communication vehicle to delineate abstract digital twin concepts for aligning stakeholders moving forward. 

The MTC supports this objective by developing a digital manufacturing demonstrator for big data solutions to enhance customer value and competitiveness towards the demands of high-volume markets. This demonstrator focusses on the rotor hub assembly line (i.e. named QM system) for the pilot production system. MTC’s Digital Manufacturing Accelerator (DMA) is used as a platform for this demonstrator to allow virtual showcasing and evaluation. With the AeroMC DMA demonstrator, Safran and the partners in the AeroMC project can evaluate and assess different digital manufacturing solutions to understand the specific benefits, outcomes, as well as required investments and maintenance.

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