Manufacturing Error-free Goods at First Time

Manufacturing Error-free Goods at First Time
Summary

The goal of reduction the number of defects is driven by several observed trends. These trends were identified before the project started, but in fact are still applicable.

The trends on the manufacturing of complex high-precision metal part can be summarized as follows:

  1. The process typically involves many complex multi-step process chains. However, still excessive and expensive finishing processes are needed in order to acquire the final specifications.
  2. The defect rates are high, typically between 1-15%, resulting in high cost prices.
  3. There is a continuous trend for more demanding specifications (higher quality, smaller features, lower costs), while simultaneously batch sizes decrease and product variety increases. This results in a smaller number of identical products, which in turn hampers the build-up of experience.
  4. The current approach to increase process robustness by applying the well-known Six-Sigma methodology to reduce defects is exhausted for these types of manufacturing processes, due to process and part complexity. A next breakthrough is needed for further defect reduction.

The MEGaFiT project aimed to create a breakthrough to face today’s global competition. This breakthrough is established by applying adaptive process control. Adaptive control is needed in situations where uncontrolled fluctuations occur which result in defects. It adjusts the process system by a control law in order to cope with these uncertainties. Adaptive process control has been applied successfully in other industries. This report summarizes the development and applications at a different length scale in manufacturing: micro-forming and additive manufacturing, both focussing on the goal of zero-defects manufacturing.

Results

In order to reduce the number of defects by adaptive process control, the relevant process variables and interactions were identified. As this was time-consuming, costly and difficult on the physical manufacturing process, this was performed on numerical models (WP3). However, as the numerical models are too time-consuming for evaluation by the real-time in-line process control, the main interactions identified in WP3 were captured in metamodels that are easy-to-evaluate (WP4).

Fast in-line measurements were developed to feed the control system with real-time information (WP5). To make adjustments in the process, actuating mechanisms were developed and the metamodels were implemented into the process control unit (WP6). All above developed knowledge and systems were integrated into the two pilot production lines in industrial settings to prove the approach to fulfil the main goal of reducing defects (WP7).

Depending on the application, these results can be applied on process lines yielding to a reduction of:

  • defects from 5-15% to below 1%,
  • cost by at least 20%,
  • material and energy consumption by at least 20%,
  • number of finishing operations by at least 35%, and, therefore, meet the objectives as defined in the proposal.

By sharing the approach via education, products, equipment, software and implementations, the results become available to other businesses within Europe (WP8) to bend the trends towards a competitive and sustainable European manufacturing industry.

More information
Web resources: http://www.megafit-project.eu
https://cordis.europa.eu/project/rcn/102138/factsheet/en
Duration: 36 months
Start date: 01-12-2011
End date: 30-11-2014
Number of participants: 17
Total budget - Public funding: 10 646 017,00 Euro - 7 150 000,00 Euro
Call topic: Towards zero-defect manufacturing (FoF.NMP.2011-5)
Instrument: Large-scale integrating project
Location
    Comment: The challenge for MEGaFiT is to make products at high quality with minimum of defects. Although the MEGaFiT team showed a huge step on this topic, the challenge stays. This because both tolerances as well as time-to-market decrease.
      Comment: The next step is to integrate more functions in parts leading to higher complexities. With the high requirements on tolerances, this will be the next challange.