We will have our next Workference on June 13 and 14 at the Fraunhofer IFAM in Bremen, Germany.
A lot of interesting topics on the agenda and experts and practitioners are meeting to discuss digital solutions for the Paint and Coatings Industry.
By Wolfram Keller (Contact), Ulf Stalmach, Ralph Wörheide
Today, raw material and paint manufacturers develop formulations based on the raw material portfolio they are familiar with. These products are intended for only one or a few market segments and applications. Finally, customers check to what extent the product meets their requirements. Especially in the case of global formulations, once a product has been developed, it is often manufactured centrally and distributed worldwide, as raw materials are usually not available in the same quality across all regions and product quality is often not identical at various production sites.
In the future, a customer will no longer just define product specifications, but requirement profiles that focus on the desired effect of the coated surface. This requires a better understanding of the parameters of the application, the properties of the coating and the underlying manufacturing and material properties.
Artificial intelligence (AI) is a powerful tool to propose several alternative options to meet the customer’s requirement profile. These options are based on an ever-growing pool of data on the origin, quality, specified and currently unknown or specified properties of the raw materials and their impact on the manufacturing process, equipment and application.
Not all of the data relevant to cover the entire value chain, from raw material suppliers to paint manufacturers and users to recycling companies and back, are generated yet. These closed data loops require a sufficient amount of relevant data, though, to ensure the quality of any machine and deep learning based simulation.
Smart companies in other industries are already using all kinds of connected technical, commercial and regulatory information to define and improve services, products, production sites and carbon footprint as well as total cost of ownership. Coatings and paints manufacturers can benefit in a similar way by collecting, archiving, using and, above all, sharing data just as consistently, i.e. thinking and acting “smartly”.
Figure D5: Centralized product development loops with AI and simulations that enable faster time-to-market and decentralized production of global formulations
By combining AI-powered predictions, simulations, and Design-of-Experiment 2.0, product development cycles and customer requirements can be drastically shortened. The operational benefits are shorter delivery times, lower total cost of ownership, resource consumption and CO2 footprint and higher customer satisfaction, e.g. by decentralizing raw material sourcing and production, even for “global formulations”.
This article is the fourth of six in our series on sustainable digitalization in the coatings industry, the concept of a Smart Paint Factory, and the Smart Paint Factory Alliance, SPFA
By Wolfram Keller (corresponding author), Ulf Stalmach, Ralph Wörheide
All industries, including coatings and their periphery, are currently confronted with various challenges, e.g., raw material shortages, Green Deal, new supply chain transparency law, and shortage of skilled labor. Solutions will change coatings companies’ value chains and ecosystems in several ways. Product development, sourcing, formulation, application, the recycling will become much more trackable, traceable, and transparent. There is no way to stay sustainably competitive without appropriate automation and digitalization.
On top to the above mentioned, transparency and reporting requirements regarding supply chain, CO2 footprint, and product safety are increasing, and skilled resources, e.g., lab technicians, data analysts and scientists are scarce. A single company is unlikely to master all these challenges on its own in a timely manner. Joining forces is a valid option. By sharing data, paint companies can establish continuous loops of information from products, services, and applications from the entire value chain. This is required to enable advanced machine learning, models, and simulations.
The concept of the Smart Paint Factory focuses on data integration within and between companies. Stakeholders must be open to exchange information and organize fast and integrated data communication in the entire value chain.
Individual coatings companies cannot master this alone. Number and intensity of cooperations with partners whose competencies and resources complement the paint manufacturers ones will increase sharply. To control the resulting flood of information and create additional value, a Smart Paint Factory is an attractive option, but it presupposes two things.
Firstly, companies must overcome their data mania. Today, internal, cross-functional sharing of data and information is a huge problem in many paint companies. The problem becomes visible when expert paint technicians or chemists are retired and their implicit, never documented knowledge is lost with them. Cross-company exchange of data with suppliers and customers is hardly imaginable. Too much emphasis is placed on know-how as the unique selling point and maintaining person-dependent knowledge despite the readiness of secure IT systems. Usage of Artificial Intelligence, AI, is an attractive method, but its deep learning models need a high volume of reliable data. Very often, this critical amount of data can’t be collected by one company only.
Figure C1: Evolution of increasingly data-based business models during
the coatings companies’ transition from “old economy” to “new economy”
Secondly, coatings companies must be willing to expand their mainly product-centric business model with key elements of digital business models. New economy companies’ business heavily depends on applied information and communication technologies for value creation or revenue generation.
In data-driven business models data are being collected, structured, and analyzed to base any kind of business-related decision, e.g., for optimization of processes, new offerings, or strategic options.
Data-centric business models are defining how new/ different types of data can support the business and create new, primarily digital offerings. Data-centric business models exceed the benefits of the other business models, but they are not applicable to coatings companies with a strong emphasis on physical products.
Each company must find its own business model “hybrid”, depending on how strong its physical core business, i.e., paints and coated surfaces, shall remain and how much it shall be supported by automation and digitalization.
This article is part of our series on sustainable digitalization in the coatings industry, the concept of a Smart Paint Factory and the Smart Paint Factory Alliance, SPFA
By Wolfram Keller (corresponding author), Ulf Stalmach, Ralph Wörheide
One difference between “new economy” and its predecessor is the shift in value creation. The production and sale of physical products like paints and coatings is more and more being replaced with virtually produced and applied products and services. Another difference is their so-called clock speed. The term describes the speed that a company can adjust to changes and is determined by the intensity of competition and the speed of development of key technologies, e.g., digitalization.
Figure B1: Evolution of annual data volume as indicator for the clockspeed of the IT industry
and driver of digital, data-driven, and data-centric business models
The evolution of IT measured by total data volume per year is dramatic. The volume of worldwide data doubles approx. every 2 years. The Zettabyte (1021 bytes) era began around 2010, reaching 80 ZB by 2020 and is expected to be approx. 175 ZB by 2025. The annual data volume will be measured in Yottabytes (1024 Bytes), if not in Brontobytes (1027 Bytes) in 2030 already.
The cycles in the coatings industry are several times longer than those in the IT industry. The greater and faster the progress in automation and digitization is becoming, the more the gap between companies in the “old economy” and companies in the “new economy” with digital, data-driven, and data-centric business models widens. Coatings manufacturers’ product-centric business models have been the method of choice in the “old economy”. The massive growth of data and increased needs to share them with suppliers, customers, and the periphery will enable faster and economically superior product development and delivery of physical products such as paint and coatings.
Figure B2: Schematic representation of the coatings industry clockspeed;
duration of eras shortening from centuries to decades until the rise of the new economy
Due to the “physical backbone” of paints and coatings, a fully blown, pure data driven or even data centric business model will not be the model of choice for raw material suppliers, paint makers, and applicants, though.
This article is the second out of six of our series on sustainable digitalization in the coatings industry, the concept of a Smart Paint Factory and the Smart Paint Factory Alliance, SPFA
By Wolfram Keller (corresponding author), Ulf Stalmach, Ralph Wörheide, June 2023
Society and industry, including the chemical and coatings industry, are experiencing major challenges, especially digitalization and sustainability. Few small- or mid-sized coatings enterprises, SMEs, have so far ventured into the task of sustainable digitization or digital sustainability. They often do not have the competencies, experience and resources of large chemical companies that started doing so in the mid-2010s.
However, other industries are much faster and more advanced than the chemical industry, of which the coatings industry is a part. The pioneers of digitalization in Germany are the ICT and automotive industries. Over the last three years, their digitization index has consistently been far higher than that of the chemical industry and coatings industry.
Figure A1: Position of “chemical industry” and “other processing industry” incl.
coatings producers relative to leaders in digitalization between 2020 and 2022
This implies a great opportunity for coatings manufacturers’ digitalization approach if they partner with companies with strengths in this area. Ubiquitous silos and a lack of willingness to cooperate are major hurdles to digitalization in many coating companies.
Up to now, the “coatings industry mantra” is the tacit knowledge of paint technicians and chemists, often acquired over decades, as well as top-secret formulations. Cautious protection of know-how, time-consuming, labor- and cost-intensive processes, and hesitation to introduce technologies proven in other industries lead to operational inefficiencies. Both, the chemical and the coatings industries are classic manufacturing and processing industries representing the product-centric “old economy”.
This article is the first out of six of our series on sustainable digitalization in the coatings industry, the concept of a Smart Paint Factory and the Smart Paint Factory Alliance, SPFA
By Wolfram Keller (corresponding author), Ulf Stalmach, Ralph Wörheide, June 2023
For several reasons digitalization and coatings industry don’t go hand in hand yet. Blaming the lack of resources, competences, and “touch-and-feel” of the virtual digitalization and the current, fast changing world is not helpful.
Instead, a clear vision, a sound benefit case, and a step-by-step implementation roadmap towards becoming a Smart Paint Factory will secure coatings companies and industry’s mid- and long-term competitiveness. The Smart Paint Factory Alliance orchestrates the development and roll-out of cooperation- and partnership-based digital and sustainable solutions. Any company along the coatings value chain and its periphery can benefit from these solutions, provided it is willing to cooperate and securely share data in its rapidly changing ecosystem as required.
We believe every coating company will have to move into this direction. How far? We are convinced that company specific targets, e.g., adopted business model, product and service offerings, and the level of sustainable digitalization will have to be individually set.
In the next weeks we will be giving food for thoughts on how to become a Smart Paint Factory and how the Smart Paint Factory Alliance, SPFA, is supporting coatings companies and their periphery in a series of short articles:
00 – Introduction to the benefits of a Smart Paint Factory and the way to get there
A – The current status quo of digitalization in the coatings industry is still poor – however, technical, economic, and ecologic potential is high
B – „New economy“ and digitalization are steeply evolving since the 1990-es – it’s time for the coatings industry to catch up
C – The digital transformation for coatings companies is a big challenge, but without alternative
D – What is “smart” in a Smart Paint Factory?
E – Joining forces and combining competences in the Smart Paint Factory Alliance
F – Examples for cross-company cooperations in the SPFA
Von Wolfram Keller (korrespondierender Autor), Ulf Stalmach, Ralph Wörheide, Juni 2023
Digitalisierung und Lackindustrie gehen aus mehreren Gründen noch nicht Hand in Hand. Es ist nicht hilfreich, den Mangel an Ressourcen, Kompetenzen und “Touch-and-Feel” der virtuellen Digitalisierung und der aktuellen, sich schnell verändernden Welt dafür verantwortlich zu machen.
Stattdessen sichern eine klare Vision, ein solider Nutzen und eine schrittweise Umsetzungs-Roadmap auf dem Weg zu einer Smart Paint Factory die mittel- und langfristige Wettbewerbsfähigkeit der Lackhersteller und der Industrie. Die Smart Paint Factory Alliance orchestriert die Entwicklung und den Roll-out von kooperations- und partnerschaftlichen digitalen und nachhaltigen Lösungen. Jedes Unternehmen entlang der Wertschöpfungskette von Beschichtungen und seiner Peripherie kann von diesen Lösungen profitieren, vorausgesetzt, es ist bereit, zu kooperieren und Daten in seinem sich schnell verändernden Ökosystem bei Bedarf sicher auszutauschen.
Wir glauben, dass sich jedes Beschichtungsunternehmen in diese Richtung bewegen muss. Inwieweit? Wir sind davon überzeugt, dass unternehmensspezifische Ziele, wie z.B. das eingeschlagene Geschäftsmodell, das Produkt- und Serviceangebot sowie der Grad der nachhaltigen Digitalisierung, individuell festgelegt werden müssen.
In den nächsten Wochen werden wir in einer Reihe von kurzen Artikeln Denkanstöße geben, wie man eine Smart Paint Factory wird und wie die Smart Paint Factory Alliance, SPFA, Lackunternehmen und ihre Peripherie unterstützt:
00 – Einführung in die Vorteile einer Smart Paint Factory und der Weg dorthin
A – Der aktuelle Status Quo der Digitalisierung in der Lackindustrie ist noch dürftig – das technische, wirtschaftliche und ökologische Potenzial ist jedoch hoch
B – “New Economy” und Digitalisierung entwickeln sich seit den 1990er Jahren steil weiter – es ist an der Zeit, dass die Lackindustrie aufholt
C – Die digitale Transformation für Lackhersteller ist eine große Herausforderung, aber alternativlos
D – Was ist “smart” in einer Smart Paint Factory?
E – Kräfte bündeln und Kompetenzen bündeln in der Smart Paint Factory Alliance
F – Beispiele für unternehmensübergreifende Kooperationen in der SPFA