COALA mapped on Manufacturing performance characteristics

The COALA solution will support the workers when performing process and product quality inspections with quality predictions and prescriptions for mitigation measures. The Augmented Manufacturing Analytics feature is A set of DIA functions interfacing the prescriptive quality analytics service connected to shop floor data sources. It will enable non-data-scientist workers to utilize and customize data analytics during product quality tests.

COALA solution for on-the-job-training using digital assistant allows the workers to meet the requirements of their work environtment: to be skilled and flexible. To keep up with continuously changing demands and to cope with altering product and process information, production workers need to adopt an approach that welcomes change. They need to be empowered by making customization transparent, enabling rapid adaptations, providing operational flexibility, and augmentation of their skills.

COALA aims to develop a cognitive advisor with dedicated human-assisted AI methods for enabling transfer of tacit knowledge of experts to novice workers. The transfer of tacit knowledge of production workers that grows with their experiences enabling them to cope with challenges of agile manufacturing.

For the change over time we expect a reduction of 15% to 30% by shortening the worker training time.

COALA is expected to impact on the productivity of employees involved in the quality detection
and repair as well as on reduction of the not detected defects delivered.

• COALA solution aims to meet manufacturing requirements regarding, e.g. time criticality, reliability (e.g. deal with factory noise, number of defects), safety when giving advice to workers, and security in business environments.
• The COALA didactic concept  will provide media materials, exercises, and competencies tests to teach factory workers and evaluate their learning progress regarding the opportunities, challenges (e.g. reliability, accuracy, and accountability of AI decisions), and risks (e.g. data security, ethical issues, and information quality) when working with AI-powered digital assistants.

• A Market Analysis (Value Chain analysis, competition evaluation, market segmentation and sizing, business expectations) will be performed to define a successful strategic positioning of COALA.
• A Business Model and Plan will be developed in order to define a go-to-market strategy and demonstrate the financial interest.

COALA solution will support workers that need to use analytics tools and new workers that perform on-the-job training. Complementary to the technology, an education and training concept that focuses on building blue collar worker competencies in human-AI collaboration will be developed. The COALA solution will transform how workers perform their jobs and it allows companies to maintain or increase the quality of their production processes and their products.

COALA solution is developed to consider following factore: factory noise, needed worker capabilities, variety of production machines, expected product and process quality, time-criticality, and worker safety.