Digitalisation of complex processes
Project challenges
Managing complex manufacturing processes is hindered by inefficient paper-based data collection, manual scheduling and inspections, costly training setups, and limited system interaction during hands-on tasks—all contributing to errors, delays, and reduced quality control.
Business challenge
Process Innovation
Digital Transformation
Skills & Training
Sector
Electrification
Technology or capability
Additive Manufacturing
Digital Manufacturing
Metrology & NDT
Simulation & Modelling
Skills & Training
Enhancing additive manufacturing with industry 4.0 technologies
As manufacturing processes become increasingly complex, the need for efficient, data-driven solutions has never been greater. MTC undertook a project to digitalise complex additive manufacturing (AM) processes, leveraging Industry 4.0 technologies to optimise operations, enhance quality control, and streamline workflow management. This initiative was supported by the Digital Proving Ground (DPG) and key technology partners: Siemens, PTC, Xerini, and Ultimo.
Project challenges
Managing complex manufacturing processes presents several challenges.
- Paper-based data collection from the shop floor is difficult to audit and analyse, leading to inefficiencies and potential errors.
- Scheduling complex processes manually is a challenge, particularly when considering maintenance and alignment with changes.
- Manual inspection of components is not only time-intensive but also subject to human error, impacting quality control.
- Building real-world training scenarios for specialist, complex assembly routines is both costly and time-consuming.
- And finally, interacting with key systems during manual handling tasks, where in-situ handheld interactions are not possible, can lead to operational downtime for data entry and interfacing.
MTC’s solution
MTC leveraged the DPG infrastructure to deploy a digital architecture, enabling risk-free experimentation and validation of digital technologies to address the challenges of managing complex manufacturing processes. Collaborating with Siemens, PTC, Xerini, and Ultimo, MTC developed an integrated digital system to enhance quality and optimisation of process management in additive manufacturing (AM).
A key component of the solution was the deployment of a digital architecture that enables real-time data traceability across multiple systems, enabling comprehensive tracking of material consumption, operator interactions, and tool usage. To further enhance efficiency, an adaptive optimisation digital twin was designed to reschedule and streamline manufacturing and maintenance activities, incorporating "what-if" scenario analysis for improved decision-making.
To ensure quality control, AI and computer vision systems were implemented to automate inspection processes. These technologies assessed powder coverage during AM builds and analysed XCT imagery post-production, reducing errors and improving inspection efficiency. Additionally, an Augmented Reality (AR) training solution via Hololens 2 was introduced, offering an immersive, repeatable, and cost-effective training experience for specialist machine operations.
To optimise shop floor operations, MTC also enhanced system interactions through a Manufacturing Execution System (MES), integrating Electronic Work Instructions (EWI) and a voice assistant for hands-free operation. These advancements streamlined workflow efficiency, reduced downtime, and improved overall productivity in the AM process.
Outcome
The implementation of MTC’s digital architecture transformed manufacturing operations by enabling seamless data traceability and part genealogy across multiple systems. Automated scheduling optimisation reduced manual effort and increased confidence in production planning, ensuring more efficient resource allocation. AI-driven defect detection significantly enhanced quality control, minimising errors and lowering costs associated with defective parts.
Training capabilities saw a major advancement with the introduction of AR-based immersive learning experiences, reducing reliance on costly physical training environments while improving knowledge retention and safety. Additionally, shop floor efficiency was greatly improved through hands-free data entry and streamlined workflows, enabling faster, more accurate data collection and minimising operational downtime.
Benefits to the client & industry
The digitalisation of AM processes delivered significant industry-wide benefits. The introduction of standardised Electronic Work Instructions (EWI) increased efficiency and consistency in manual processes. The elimination of paper-based inefficiencies improved traceability and reduced data loss. Optimised scheduling led to increased machine availability and operational efficiency, while automated scheduling reduced the time and effort required for manual scheduling, increasing confidence in production planning. The use of virtual training environments lowered training costs, reduced reliance on physical setups, and improved learning outcomes through interactive and immersive experiences. Health and safety were also enhanced by minimising risks in practical training scenarios. Early defect detection helped reduce costs associated with defective parts, while automated data analysis improved the efficiency of quality assessment activities. Hands-free data collection streamlined workflows and enhanced operator productivity, and the secure deployment of AI ensured trust and security in operational processes.