Integrated information for improved quality demonstrator (IIQ-D)
Project challenges
Costly and time consuming data interpretation, manual data re-entry and duplication of effort are common when one software cannot consume what another produces, and many opportunities for process improvement are missed.
Business challenge
Product Innovation
Sector
Aerospace
Technology or capability
Digital Manufacturing
Manufacturing Systems
Metrology & NDT
Process Design
Project Challenges
IIIQ-D was a CRP project sponsored by many companies.
This was the last project in a long chain of CRPs that developed various parts of an end to end digital thread, connecting design, engineering, manufacturing and inspection processes.
Projects such as, PLM Integrated measurement planning (3 phases), Intelligent Advanced Metrology Cloud (I AM cloud) Digital Measurement Planning (DMP), Integrated Information for Improved Quality (IIIQ), all laid building blocks for IIIQ-D.
It’s still (6 years on) one of the most advanced demonstrations of digital manufacturing out there, and bits of it have been used as inspiration to many other projects over that time.
Every stage of the manufacturing process chain is important to the final quality of a component. Each process produces and consumes data and information that adds value somewhere else in the chain.
Traditionally, when those processes cross discipline boundaries, such as design to manufacturing or manufacturing to inspection, valuable information is lost or not transferred effectively.
Costly and time consuming data interpretation, manual data re-entry and duplication of effort are common when one software cannot consume what another produces, and many opportunities for process improvement are missed.
Linking cross discipline information together requires a digital thread. A trusted end-to-end system of digital technologies passing critical information along the process chain.
MTC's Solution
- A manufacturing system was formed containing a CNC milling machine and on-machine, in-line & end-of-line inspection equipment.
- A digital thread of design, manufacturing, inspection and analytics technology, was configured for the system covering the entire process chain.
- A wheel hub test part was designed using Model based definition (MBD), a 3D model with metadata, fully defining the authority design specification.
- The MBD, managed in PLM, was passed along the full process chain including CAM and inspection programming.
- Multiple batches of the wheel hub were produced and inspected and embedded sensors recorded live machining data during production.
- The manufacturing data was traceably connected to the MBD features and inspection results in a visualisation tool for decision support and process improvement that highlighted the benefits of digital manufacturing
IIIQ-D is demonstrating the power of combining model based definition, inspection and process planning and manufacturing metrology with intelligent informatics and interoperable data exchange through digital workflows.
Simon Todd, Technical Specialist - Measurement Process Owner – Rolls Royce
The Outcome
- Validated, fit for purpose MBD models at multiple stages of manufacturing (Authority, Process, Inspection).
- System integration with a product lifecycle management (PLM) platform.
- Inspection programming from MBD.
- Automatic point cloud evaluation from MBD.
- Feature based results traceably linked to MBD.
- Feature based manufacturing parameters traceably linked to results and MBD.
Benefits to the Client
- Useful information communicated to the right departments for addition of domain expertise, re-using data and improving process planning. Resulting in manufacturing processes capable of achieving functional design requirements.
- Revision control and enhanced data management through a trusted PLM platform.
- Reduced time spent inspection programming. Reduced manual data entry and improved standardisation of programs.
- Consistent and standardised measurement strategies.
- Contextualised results and statistical process control (SPC) reported, enabling concessions teams to investigate and assess impact of failures.
- Trusted data for root cause analysis, enabling decisions for improvement of manufacturing processes or more efficient inspection processes. Improved quality or more efficient production
