Leveraging innovative new information technology tools such as artificial intelligence (AI) and machine learning (ML) has the potential to offer myriad benefits to the coatings industry. One particular application of the technology utilizing “data mining” or “Big Data” capabilities of modern IT has attracted the attention of the American Coatings Association. This is the use of AI and ML within an “innovation algorithm” that can read journals, formulation and testing data, and other technical content using natural language processing to streamline and enhance research and development. Specifically, ACA is interested in helping its member companies develop enhanced knowledge of the properties of the raw materials being used or considered in the product development process.

In discussing how ACA could help formulators stay abreast of developing technical, health, and environmental information on critical paint raw materials, the association’s Science & Technology Committee explored a number of possible initiatives. One promising program that is now underway—known as the “Big Data” project—emerged as a result of tracking innovation management research at North Carolina State University. Members of the Science & Technology Committee have been in collaboration with NC State’s Center for Innovation Management Studies on the Big Data project, which is funded by ACA through a grant to the university. The project’s Industry Advisory Board includes Axalta Coating Systems, The Sherwin-Williams Company, PPG Industries, BASF, AkzoNobel, Dow Coating Materials, Covestro, Eastman, and Wacker, according to Steve Sides, ACA’s vice president, Global Affairs and chief science officer.

ACA is interested in helping its member companies develop enhanced knowledge of the properties of the raw materials being used or considered in the product development process.

The focus of the project is to provide “actionable intelligence” for coatings scientists and product stewards by offering customized software that can sift and sort a rich trove of publicly available data that has been “collated and curated” to support analysis. Using customized software tools and detailed algorithms, the project is constructing a system that performs periodic “scraping” of more than 200 websites that focus on topical areas including government, public, professional, science, social media, and advocacy. “This tool will bring the power of Big Data to assess our chemistry in terms of regulatory or public perception risks by tracking health- or environment-related terms associated with the chemistry. The aim is to spot trends such as movement from early academic reports of health effects into social media and traditional media sources or vice versa, and to give industry early warning signs when a chemical may be under pressure or restricted,” states Beth Uhlhorn, global product sustainability leader at Dow Coating Materials. “The goal,” adds Sides, “is to create a frequently updated, collated, and curated, searchable corpus of data on environmental and public health references associated with common chemical raw materials used by the industry.” The resource is expected to eventually support paint and coatings research and development, chemicals management, and industry advocacy efforts.

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ACA’s Big Data project was started in concept about five years ago, but is currently in year two of a three-year research grant that is developing the resource tool, according to Sides. The project first went through an initial “proof of concept” phase, and then a “pilot project” demonstrated the functional utility of both the associated data collection and analytic software. Currently, in Phase 2 of the project, a full-scale demonstration model is under development, which for the first time will integrate the full targeted data set and reference a completed list of chemicals under consideration. “ACA members, and specifically formulators and product safety specialists, will be able to use this resource tool to make more informed decisions for their product innovation and stewardship efforts,” Sides notes.

The focus. . . is to provide “actionable intelligence” for coatings scientists and product stewards by offering customized software that can sift and sort a rich trove of publicly available data that has been “collated and curated” to support analysis.

While still a research project, the goal is to offer the members access to both the data and the analytic software. “The current plan is to explore how this might be done on a subscription basis in order to collect required revenues sufficient to maintain and continuously update the resource,” comments Sides. ACA staff will also be able to access the tool to support issue management on behalf of the members.

Sides stresses, however, that it is important to note that any resource tool developed will need to be used by subject matter experts to access and interpret the collated and curated data. “This resource is not an ‘Oracle of Delphi’ to advise on all things, but is intended to be a key research resource that is intended to allow for more informed (subject matter expert) decisions that align with company-specific criteria, goals, and objectives,” he asserts.

CoatingsTech | Vol. 16, No. 9 | September 2019