WHY SPONSOR?

Participating at the Manufacturing Indaba is an ideal way to position your company as a market leader at this premier event. By sponsoring, you will showcase your brand optimally and generate great brand awareness. Manufacturing Indaba provides a major networking platform for decision makers and professionals within the Manufacturing sector.

For further information on sponsorship options, please contact Liz Hart on +27 11 463 9184, +27 71 844 2569, or click here to e-mail

TOP REASONS TO SPONSOR:

  • Meet qualified buyers in a highly targeted environment
  • Generate valuable sales leads
  • Strengthen relationships with existing and loyal customers
  • Test or launch new products
  • Meet important retailers, service providers and vendors
  • Keep up-to-date with your competitors’ developments
  • Showcase your full range of products
2018 SPONSORS

NAME BADGE SPONSOR

Deloitte is one of the Africa’s leading professional services firms; providing Audit, Tax, Consulting, Risk Advisory, Business Process Solutions and Corporate Finance services to clients across the continent. We service clients across industries that include manufacturing, retail, telecommunications, mining and the public sector. We operate through over 8000 skilled people across 29 offices in Africa to service 53 countries across the continent.

Our value to clients lies in making an impact that matters as we draw on unique service combinations, while we understand and evaluate our clients’ issues broadly and deeply. By working together in multifunctional teams, our professionals are able to share knowledge and ideas to develop solutions that are tailored to each client.

EXHIBITION REGISTRATION COUNTER

DataProphet is a data science company specialising in predictive and prescriptive machine learning solutions within the manufacturing industry. Behind DataProphet’s success is a strong team of thirty data scientists, with diverse skillsets in Engineering, Computer Science, Statistics and Actuarial Science.

Our solution, OMNI, is targeted towards complex, multi-step industrial manufacturing processes, utilizing an advanced form of supervised and unsupervised machine learning to:

  1. Predict defects, faults or any quality issues with a product.
  2. Identify high yield operating regime.
  3. Perform quality control tasks using computer vision on every product.

With the ability to learn from historical production process data, OMNI automatically finds the optimal set points for variable process parameters within their control limits to maximise the output yield. The solution takes into account ambient features and understands how different process parameters interact with each other through the successive steps in the manufacturing environment.

OMNI can then, for any new production batch, serve optimal parameters learnt from previous experiences and account for process drift occurring in the natural manufacturing environment (e.g. regular machine wear).

Currently deployed at numerous manufacturing sites globally, OMNI has consistently increased yield and reduced scrap rates. In each case, the results are quantifiable at a financial level.