Industry 5.0 Ready for Manufacturing?
In the Industry 5.0, technology associated to Industry 4.0 must address emergent requirements for learning, continuous improvement, sustainability, circularity, disruption and innovation. We are still far away from full implementation of the Industry 4.0 across the entire supply chain in manufacturing because we struggle with standardization, communication infrastructure and availability of digital competences. Delayed deployment of Industry 4.0 technologies is an opportunity to embrace Industry 5.0 principles and include them in the design right from the beginning. There are no short cuts to digital transformation but the benefits are worth to start the journey.
Are we Industry 4.0?
Industry 4.0 term has already been around for more than a decade since German government publicly introduced it at the 2011 Hannover Fair, as a high-tech strategy for computerization of manufacturing. Industry 4.0 is focused on automation and digitalization to increase efficiency and flexibility of production. Success stories about 4.0 usually come from automotive, pharmaceuticals, electronics and aerospace domains, which historically have always been driving, demanding and absorbing high-tech innovation. Basic 4.0 ideas, like robotics and automation, have mainly taken over heavy, difficult, dull, unsecure and repetitive work. Technologies like blockchain are quite successfully pioneered by the fin-tech companies, however AI-driven technologies, even the classic correlation-based artificial intelligence (weak AI), seldom finds practical application in manufacturing. This is because the full horizontal and vertical integration of AI technologies across manufacturing supply chain, especially at small and medium-sized enterprises, craft manufacturers, or traditional industries, as aimed for in Industry 4.0, is still far from reality.
Challenges for Industry 4.0
Many small and medium manufacturing enterprises are slowly adopting those Industry 4.0 technologies, which became more accessible and affordable. The speed of transformation depends on how well company can deal with two type of challenges. On a technical end, companies struggle with standardization. There is hardly a standardized approach in describing manufacturing processes and workflows to enable optimization and highlight spots, where data can be captured and converted to information. When process is optimized and ready for digitalization, mixed machinery park is rarely a unified ecosystem with standard protocols for data exchange across different machine types, brand and age. Latest machines with full digital capabilities and installed operating systems can already be considered IIoT products but they need modern communication infrastructure to transfer relevant data across operating and IT networks. Without process optimization, approval for investments in equipment and infrastructure upgrade can be difficult. This leads to non-technical challenges. Traditional industries struggling with crafting a clear vision for their own digital transformation journey. Without digital strategy it is harder to attract digital talents and digital professional rather gravitate to high tech domains instead. This automatically reduces capability to develop in-house solutions designed for unique manufacturing processes (which are rarely optimized for digitalization) and amplifying potential to create new value. Investments become limited to absolute must-have established IT products and the problem is, that those products have already evolved and became commodities serving wide range of generic processes. Affordable to implement, they can only address a friction of real customer needs and customization is limited and expensive.
What Industry 5.0 can offer to manufacturing?
Industry 5.0 is not based on technologies. It is focused on humans, sustainability and social responsibility, and not on productivity and efficiency alone. In Industry 5.0 the design of digital solutions should support people's needs. For example, the primary focus of robotics and automation should be to allow people to perform more meaningful tasks, that are specific to human sensitivity and require different skills like judgement of a situation, decision making or creative improvements. Collaborative robots (cobots or lightweight robots) can work together with operators in synchronized and secure environment. Technology, designed for specific workflow can automatically shift tasks between human and cobots. In Industry 5.0 data transmission is expected not only to be fast but also energy efficient, secure and manageable. We just highlighted the need to upgrade the infrastructure. However, big data can become a problem, unless you develop tools and methods to convert data streams to meaningful information, which serves as learning platforms for continuous improvement. Operators should be supported with systems, which can find correlations among complex data sets from different sources (process, sensors, quality, etc.) and then use the data to take decisions about efficient use of natural resources necessary to make the products (energy, materials). Engineers could use more advanced, narrow expert systems, with artificial intelligence and machine learning technologies. Those systems enhance their knowledge and experience with causality-based effects outside typical correlations to enable sustainable design and simulation of tools and processes for industrialization.
How to take on Industry 5.0, when we haven't embraced 4.0 yet?
Delayed adaptation of technologies associated to 4.0 in traditional manufacturing domain can become an opportunity if Industry 5.0 concepts and values are included it in the design. Methodologies like design thinking allows to address human centric emerging requirements (sustainability and social responsibility) and adopt 4.0 technologies meeting those requirements. High tech OEMs, as already mentioned, are used to absorb innovation, so they naturally expect traditional manufacturing to follow latest technologies associated to 4.0. Robotics and automation must improve repeatability of processes, and data exchange must be used for superior quality and traceability of products. Customers start to include factors like sustainability and carbon footprint in their purchasing decisions. New needs will require manufacturing companies across the entire supply chain to collaborate and exchange information in order to manage necessity for circularity without giving up on quality and properties. In order to assure data exchange at scale, enterprises interested in developing data driven services, must initiate standardization of communication architecture and exchange protocols. This can help automation of workflows, integration of robotics and compatibility with interconnected sensors, instruments, and other devices networked together with computers' industrial applications. High quality impact data can be available to develop new ideas and design applications customized for specific manufacturing workflows and energy management processes beyond long-established and commodity systems. This creates opportunities for small and medium manufacturing enterprises to design digital solutions, which are unique for their value chain creation and can address needs of their employees and their customers.
No short cuts to Industry 5.0
My experiences from building digital offerings for familiar EPP domain (ultralight expanded polypropylene) told me that, there are no short cuts in deploying Industry 5.0 in small and medium manufacturing. Success of Industry 5.0 depends heavily on the design. Deploying principles of design thinking, rapid experimentation, prototyping and co-creation with customers helps to set the direction and craft the vision of digital offerings. Those techniques are essential to illustrate to the C-suite a job, your product helps customers to accomplish. This is elementary requirement for any disruptive innovation. Disruptive digital innovation can attract digital talents, who can gravitate from IT domains to more challenging opportunities in manufacturing. Having digital competences in house enabled a great deal of agility and speed in experimenting, building fast prototypes, and deploying multiple iterations for testing. For example, in house digital competences allowed us to turn production equipment to IIoT and start experimenting with real data converted to information useful for operators' workflows. Small experiments gave good indication about how big data might impact the performance of the application after it scales in the future. Experimenting and rapid prototyping organically thought us how to decide between buying and building particular technology components. If we would have taken a short cut few years back and decided to hire software company to build what we thought we wanted then, we would end up already available out-of-the-box solution. It might have promised something intelligent or smart and it might even improve productivity and efficiency of some processes. However, except from generic functions it would never be able to address new opportunities to differentiate your digital offering towards employees and customers.
Benefits of developing Industry 5.0 solutions.
The solution we had in mind was a data management ecosystem, dedicated to producers of ultralight EPP components, who needed to improve quality of their products and make the use of natural resources more efficient (materials, energy, CO2 footprint). Our technology links physical and digital assets from manufacturing equipment and offers operators and engineers functions supporting processes and workflows unique for EPP domain. The key to successful deployment of design thinking approach was to get process engineers working together with software developers. Process teams had profound understanding of manufacturing workflows and customers’ needs, so they knew what information was needed. Software developers on the other hand, were able to build functions necessary to convert available data to information, which engineers were looking for, keeping an eye on the future architecture. After basic functions were developed, technical sales team could step in and involve customers in the design. Brining customers so early allowed to validate our hypothesis about the real benefits. Experiences gathered before during prototyping phase by engineers, software developers and technical sales helped all of them to moderate later discussions with customers. Customers and users were able to discover functions essential for their workflows by themselves and our in-house team was flexible and quick in adapting our design. Creating an ecosystem for smart and analytical operators requires understanding of workflows and discovering where and how technology can support people in achieving better results and make their job in manufacturing more interesting. Operators with enough experience and right set of skills are extremely helpful during the design because they know, where additional information enables informed decisions leading to sustainable results, i.e. continuous improvements for carbon emission and material consumption reduction.
There many more benefits I could write about here, but I think the biggest one is, that starting digital initiative with strong focus on Industry 5.0 principles driven by 4.0 technologies allows you to discover hidden potential to create new value for employees and customers. Starting a digital transformation journey also exposes your organization to a broad range of new opportunities for cooperation with other companies from different domains, who might have developed something, which is not commercially available yet but might perfectly fit your objectives. It is not guaranteed that you get your design right for the first time, but experimentation with technology, processes and people will provide clarity on what is that you want to build and how your digital offerings can differentiate your business proposal in the digital economy.
What is your approach to Industry 5.0? Feel free to connect with me to exchange views and ideas.