Best practices for human-machine collaboration with Amir Ben-Assa, VP Marketing & Product Strategy, Plataine
Artificial intelligence and machine learning are incomparable in their ability to extract insights from immense datasets. But, in most cases, humans remain far better at understanding the context of those insights and the subtle variation of their meaning. The field of smart software, smart machines and cobots (collaborative robots) demonstrated dramatic technology advancements in recent years, so dramatic that the manufacturing sector cannot ignore.
Artificial Intelligence (AI) is not just a technological trend, but a real paradigm shift in the way companies operate and grow. However, despite the impressive achievements of AI in the fields of speech recognition and generative AI, many manufacturing companies are still hesitant to integrate this technology into their processes. The reasons for this are various. Sometimes this is due to a lack of knowledge, or a fear of the unknown, and often to the challenges associated with implementation. Let’s explore the basics of human-machine collaboration, and especially why its adoption is crucial, what role AI plays in it, and what steps are important for successful implementation, increased efficiency, innovation and competitiveness.
What is human-machine collaboration?
Human-machine collaboration is the way that humans and automated technology work with each other to reach a common goal. This can take many different forms. Most commonly, it involves having workers and robots collaborate on the same production line. Another example is when human experts review and verify the outputs of AI or machine learning models, adding their own knowledge and expertise, and helping to train AI to deliver better outputs over time.
Human-machine collaboration is the result of a series of different stages of how humans and machines can interact with each other. If we take the example of workers and robots collaborating on the same production line, the following stages can be outlined:
Strict separation of work areas: In traditional industrial plants, robot systems are strictly separated from human workers. They have their own cell, which is clearly demarcated by a protective fence and which people generally do not enter. If this happens, operations will cease.
Coexistence: In this case, there is no need for a protective fence. Nevertheless, humans and machines have different work areas. They don’t work together.
Cooperation: Humans and industrial robots working in cooperation share the same workspace. However, they do not work together on a product, but rather at different times.
Collaboration: Here, humans and robots work hand in hand. They work on the same component at the same time in a shared workspace.
What is in for you?
Human-machine collaboration makes it possible to look at automation in an entirely new way. Rather than simply automating work completed by human teams and cutting costs, it uses technology to augment human intelligence, prioritising high-value outputs over immediate cost savings.
It lets you make the most of the expertise and knowledge your team has developed over the years – freeing them from routine, mundane tasks and empowering them to focus their time and efforts where it is most valuable to the business.
For now, there are limits to what AI and machine learning alone can deliver. Human-machine collaboration in manufacturing adds the all-important human verification layer. It is essential for ensuring that whatever conclusions your AI draws from the data you feed it with, they are properly translated into the right outputs for your customers.
How AI improves collaboration and enhances experience
AI has profoundly transformed collaboration on the factory floor, enhancing the overall experience for individuals and teams.
Enhancing efficiency and decision-making
AI improves efficiency as it automates repetitive tasks, allowing humans to focus on more complex and creative work. AI analyses large datasets quickly, providing valuable insights for decision-making, therefore allowing workers to be more efficient and complete more tasks per shift. AI processes vast amounts of data to identify patterns and trends, aiding in more informed decision making. Generative Pre-trained Transformers (GPT) such as ChatGPT provide real-time information and suggestions, facilitating faster and more accurate decisions. AI-powered analytics help predict outcomes, allowing for proactive data-driven decisions and preventing errors.
Regarding communication, AI-powered language models including ChatGPT enable natural language interaction, making communication more intuitive and efficient. For example, they can translate languages in real-time, breaking down language barriers and facilitating global collaboration. AI also enhances accessibility by providing alternative communication methods for those with disabilities.
Revolutionising human-machine interactions
With AI, humans can communicate naturally, speaking and interacting with software and hardware as if they were humans. AI tools understand the context and can respond appropriately, creating a seamless interaction experience.
AI permits personalised experiences, analysing user behaviours and preferences to deliver personalised recommendations and experiences. ChatGPT tools can tailor responses based on user inputs, creating a more engaging and relevant interaction.
AI can also augment human creativity by suggesting ideas, providing inspiration and digital assistance in the creative process. Natural language processing tools can generate content, freeing up time for humans to focus on more innovative tasks.
AI is revolutionising human-machine collaboration by enhancing efficiency in real-time, improving decision-making and transforming the user experience. With AI, humans can communicate more naturally and effectively, leading to a more productive and satisfying collaboration between humans and machines.
Benefits of human-machine collaboration
Collaborative robots play a central role in Industry 5.0 as they represent an enabling technology that allows effective and safe collaboration between humans and machines. Here are some ways that human-centred robotic automation can benefit businesses.
Greater productivity and efficiency
By integrating collaborative robots into work tasks, companies can automate repetitive and strenuous tasks, allowing human operators to focus on more creative and strategic tasks. This increases the overall efficiency and productivity of the organisation as more work gets done.
The work is fast and precise.
Reduction of errors
Collaborative robots are known for their precision and consistency in completing tasks. By eliminating or reducing human errors, automation can significantly improve the quality of the products or services offered by a company, thus increasing customer satisfaction and reducing repair or quality control costs.
Adaptability and flexibility
Human-centred robotic automation allows businesses to more easily adapt to market changes or new customer requests. Collaborative robots can be easily rearranged or reprogrammed to perform new tasks or adapt to new manufacturing processes, enabling operational agility that can be a crucial competitive advantage.
Improved safety at work
By integrating collaborative robots into operations, companies can reduce the risks associated with dangerous or physically demanding tasks for human operators. This results in a safer work environment and can help reduce occupational injuries and illnesses, thereby reducing the costs associated with sick or disability leaves.
Greater employee involvement
When human operators find themselves collaborating with robots, they often find greater gratification and satisfaction in their work. Automation can alleviate repetitive and tedious workloads, freeing employees to focus on more challenging and creative tasks. This can lead to greater loyalty to the company, reduce absenteeism and increase the feeling of belonging to a team.
Resource optimisation
Robotic automation allows companies to use resources more efficiently, including labour, time and materials. This optimisation can reduce production costs, enhance production schedules [1] and improve inventory management, therefore contributing to greater competitiveness in the market. In short, human-centred robotic automation results in a safer, more efficient work environment, with happier and more productive employees.
These combined advantages can help companies become more competitive in the market by better adapting to changing customer needs and delivering high-quality products and services promptly.
A significant impact in composites manufacturing
The integration of human-machine collaboration already has a significant impact in the composites industry, leveraging AI tools and robotics to streamline production processes, improve quality, sustainability standards and ontime delivery. Here are a few examples outlining the advantages of human-machine collaboration:
- Automatically generating pick lists to use the existing material inventory optimally enhances efficiency and resource utilisation.
- The integration of robotics into the composite manufacturing process streamlines sorting and picking of prepreg materials, improving productivity and precision while reducing manual labour and error margins.
- AI-powered scheduling in composites manufacturing orchestrates tasks with one click, creating an optimised production plan that maximises resources utilisation. The automated solution enables factories to scale and maximise yield and sustainability.
Human-machine collaboration and constant changes in the corporate world
In an increasingly digital world, we will see a massive raise in automation driven by robotics and machine learning. This will have a negative impact on low-skilled manual labour. However, in parallel, this will be accompanied by an increased demand for highly skilled workers to maximise the benefits of the digital age as their capacity grows.
After all, it is humans, not technology, who will continue to provide innovative new ways of working, strategic thinking and brainstorming. This will clearly lead to greater demand for highly skilled people, and we may risk a skills shortage unless we can increase the upskilling or training of the workforce. The rapid and ever-increasing pace of the digital world means that lifelong learning and continuous change will be the defining characteristics of employment in the future.
So where will the new jobs come from?
It is safe to say that, by 2030, there will be new types of roles that are not yet known. In their “Realizing 2030” survey [2] on the future of technologies and human-machine partnerships, Dell Technologies and the Institute for the Future estimate that 85% of jobs in 2030 have not yet been invented.
Job growth will be seen in areas such as software and application development, to take advantage of the digital age. But also in roles for the inspection, quality control and auditing of new digital assets. Roles such as data scientists and big data analysts are also needed to generate AI insights from the vast amounts of data produced. Furthermore, the digital age will lead to a more service-oriented economy, and many service jobs will be created through these new digitally-enabled services.
Human-machine collaboration in the warehouse
Human labour often remains indispensable in the warehouse. People are capable of performing complex tasks that cannot yet be fully undertaken by machines. For example, they can identify incorrectly stored items and classify damaged products.
Through the interaction of humans and machines in order picking, the strength of both sides can be optimally utilised: machines perform repetitive, tedious or time-consuming tasks while humans use their cognitive skills to solve problems and produce higher-quality work.
Human-machine collaboration in order picking also has its benefits for workers. The use of machines eliminates a number of physically-demanding tasks, which in turn can reduce workplace accidents and injuries. Workers are able to focus on more demanding tasks and can make better use of their skills.
Overall, human-machine collaboration in order picking allows for more efficient and accurate order fulfilment. By making the most of the strengths of both people and machines, the warehouse can become more productive while improving the working conditions of employees.
Shaping the future of automation
The transition from traditional automation to collaborative systems does not mean the end of the former, but rather an expansion of the automation toolbox available to industries.
While traditional automation shines in high-volume, unchanging production environments, collaborative automation excels in dynamic environments where flexibility and adaptability are critical.
Regarding cost implications, traditional systems often require a higher initial investment and infrastructure overhaul. In contrast, collaborative systems offer lower entry costs and can be integrated into existing workflows with minimal disruption, leading to reduced costs in the end.
Finally, it also has an impact on skills development and job satisfaction, as collaborative automation opens up ways to upskill the workforce, creating more engaging and less monotonous jobs.
The choice between traditional industrial automation and collaborative automation is not binary, but contextual. As industries strive for efficiency, adaptability and human-centred approaches, collaborative automation emerges as a complementary force, not a replacement, for traditional systems. Understanding their differences and synergies is critical for companies navigating the complex landscape of modern manufacturing.
Industry 5.0: towards a revolution in manufacturing
Throughout history, the evolution of the industry has been a constant journey of technological advancement and adaptation. From the industrial revolution to today, we have witnessed how technology has transformed the way we produce goods. Industry 5.0 is the final frontier of this evolution and promises to revolutionise manufacturing in ways we could only imagine a few decades ago.
Industry 5.0 is the natural evolution of Industry 4.0, which is focused on automation, digitalisation and interconnection of devices and systems. Industry 5.0 goes further by reintroducing the human factor into the manufacturing process, redefining the relationship between machines and workers. It seeks greater collaboration between workers and machines. Advanced technologies such as exoskeletons, collaborative robots and augmented reality allow workers to interact directly with machines more safely.
The future of manufacturing
Human-machine collaboration marks an exciting new chapter in manufacturing, where technology and the human factor combine to create a more efficient and sustainable production environment.
However, to make the most of this revolution, companies and governments must invest in technology and training. The ability to adapt and adopt these new trends will determine the future success of manufacturing in the Industry 5.0 era.
References:
[1] www.plataine.com/blog/productionscheduling- in-the-industry-4-0-era-aibased- digital-assistants-can-providevital- support
[2] www.delltechnologies.com/ content/dam/delltechnologies/assets/ perspectives/2030/pdf/Realizing- 2030-A-Divided-Vision-of-the-Future- Summary.pdf