Problem: Modern factories are unnecessarily inefficient. A typical factory operates at only 66% productivity, which can cost industrial manufacturers an estimated $50 billion annually. Factories are wasting energy, water and raw materials, while simultaneously contributing with 56% of global greenhouse gas emissions. That does not mean factories are not utilizing technology. With the rise of Industry 4.0 factory owners have begun equipping their facilities with sensors to collect production data across all kinds of assets. Unfortunately, these same factories are not prepared to utilize these massive amounts of data for smarter and sustainable operations and hence manual analysis is impossible. The good news is that automated methods utilizing Artificial Intelligence have shown exciting potential for tackling this problem. Unfortunately, current solutions available in the market require too many resources and too much high-tech competency for factory owners to implement. Nor can these available solutions provide the level of insight necessary for factory owners to trust and deploy at scale. Modern factories need a solution which can easily integrate with their existing data acquisition systems and identify bottlenecks in the production process without requiring expert intervention.
Society: Managing operations in an environmentally and socially responsible manner – “sustainable manufacturing”– is no longer just nice-to-have, but a business imperative. Companies across the world face increased costs in materials, energy, and compliance coupled with higher expectations of customers, investors and local communities. Most of the Fortune 500 companies have already started to take important steps towards green growth – ensuring their development is economically and environmentally sustainable. However, many manufacturing companies (having a big share of the global greenhouse emissions simply due to heavy usage of fuels for energy) have not yet embraced these great opportunities. Industrial manufacturing accounts for almost 56% of the total greenhouse gas emissions in the world. Examples show that artificial intelligence can reduce energy and CO2 emissions with as much as 40% without reducing productivity or quality. Insight generated using Intelecy advanced analytics engine can be used to identify what process steps contribute most to the total CO2 emissions and best possible measures can be devised to minimize greenhouse gas emission.
Objectives:
The overall objective of the DATASET project is to mature, scale-up and demonstrate Intelecy with reference customers in different countries. The specific objectives of the SME Instrument Phase-2 will include:
- Testing and demonstrating the system with customers in different regions and industrial vectors, to continuously improve the user experience and shorten the on-boarding process for new customers.
- Enabling integration of Intelecy with market leading control systems which will increase our TAM by 5-fold.
- Demonstrate and document the benefits of these improvements with at least 5 end-users outside Scandinavia to increase market awareness and make the system ready for international market roll-out.
Conclusions:
Development, integrations, testing and demonstration has been successful, but because of the global COVID-19 crisis demonstrations outside of Norway has not been possible. But gladly Intelecy has been able to expand into new industry verticals such as metals, minerals and mining.
