About COALA

COALA will provide a solution for cognitive assistance that consists of a composition of trustworthy AI components with a voice-enabled digital intelligent assistant as an interface. The 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.

Objectives

Objective 1


Reduce the number of quality
incidents in manufacturing.

Objective 2


Reduce the time needed for on-the-job
training of workers in manufacturing.

Objective 3


Overcome barriers and reduce scepticism regarding the use of a voice-enabled DIA
in manufacturing environments.

Objective 4


Improve the competencies of blue-collar workers in managing AI opportunities, challenges, and risks in the shop floor.

Industry Scenarios

COALA plans to demonstrate its solution in three complex and highly dynamic manufacturing domains that are confronted with the megatrend of Industry 4.0, but are characterized by different peculiarities and thus are a perfect fit to demonstrate the full potential of the COALA concept.

Textile
Production

On-the-job training of new machine operators

White Goods
Production

Quality inspection during Zero Hour Testing

Detergent
Packaging

On-job training of new and temporary line managers, change over, issue handling

Augmented Analytics


Besides robotics and autonomous vehicles, an emerging field in the AI domain is Augmented Analytics (AA), which uses AI to make data analytics accessible for the masses. Allied Market Research estimates the global AA market will grow to almost 30 billion Euro by 2025. Key players are mainly large US companies, such as IBM, Microsoft, Salesforce, and Qlik. AA is a transformative approach that utilizes AI to support humans in tasks that formerly required expertise in data science. Especially marketing-, sales-, and finance-related tasks currently benefit from AA. Key technologies of the AA sector are (digital) voice assistants and chat bots that interact intelligently with humans via natural language – these AI-driven programs guide their users through complex analytics processes. In the manufacturing domain AA is hardly recognizable today. Its main application potential is the support of knowledge intensive activities that have significant impact on product and process quality.

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Besides robotics and autonomous vehicles, an emerging field in the AI domain is Augmented Analytics (AA), which uses AI to make data analytics accessible for the masses. Allied Market Research estimates the global AA market will grow to almost 30 billion Euro by 2025. Key players are mainly large US companies, such as IBM, Microsoft, Salesforce, and Qlik. AA is a transformative approach that utilizes AI to support humans in tasks that formerly required expertise in data science. Especially marketing-, sales-, and finance-related tasks currently benefit from AA. Key technologies of the AA sector are (digital) voice assistants and chat bots that interact intelligently with humans via natural language – these AI-driven programs guide their users through complex analytics processes. In the manufacturing domain AA is hardly recognizable today. Its main application potential is the support of knowledge intensive activities that have significant impact on product and process quality.

Knowledge-intensive activities are critical for a business and their management is oftentimes an important factor to gain or maintain competitive advantage. These activities are difficult to automate and companies that rely on them are expected to increasingly suffer from labor force shortages caused by the demographic change and the growing cognitive requirements for people employed in an Industry 4.0. This has a significant negative impact on the value creation in this industry that must stay competitive globally. Retirement and job change is a constant challenge at the factories with the experienced workforce in Europe. Similarly, the process industry has to replace retired, very experienced workers in some cases, after 30-40 years of employment at the same site. The total cost of the new workers’ development is significant and with the production loss, it can reach tens of thousands of Euros. Immigration to the EU can partially address the demographic problem but oftentimes the education of foreign factory workers is an issue.

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