Manufacturing productivity challenge

Leonardo ITG is seeking innovative solutions to help manage complex processes with many variables and secure the harvesting, storage and analysis of manufacturing data.

About the challenge

There is an urgent need to improve the productivity in manufacturing to hit a key delivery milestones.

Killer issues

  • Secure harvesting, storage and analysis of manufacturing process data
  • Complex processes with many variables

Background

Our range of physical products are typically produced in batch quantities from 1-100 units and normally configured for each customer. The economic benefit ‘perfecting’ manufacture or automating the process is not there.

On the positive side, we have an abundance of process information. This information is stored in many locations, across applications, networks and retained either digitally or hard copy. There is a distinct probability we don’t know all the information we hold or what’s relevant.

Detail

Yield has dropped off in previous months.  A number of possible causes exist - some of which are currently not well understood but which fall into the following umbrella categories:

  • Supplier issues
  • Manufacturing process deviations
  • Limitations in test methodology
  • Latent issues in design

It is thought that the root cause(s) could be found and alleviated through exploitation of machine learning.

Project phases

  • Requirements capture and concepting
  • Development and proving
  • Demo and handover

Evaluation criteria

  • Exploitation of machine learning
  • Coherence and efficacy of trial results
  • Cost of implementing the solution
  • Scalability of solution
  • Level of specialist skills required to support the solution
  • Security of information held/processed by the solution

Project deadline

Project to be fully completed by end of November 2020.

Proposal Submission Deadline is 15 July 2020.