When and how to leverage workforce dynamics when adopting technologies
How to keep the workforce engaged and developing as we continue to implement Industry 4.0.
- Build a training culture that is flexible, economically sustainable and attracts and nurtures top talent.
- Understand the interplay of three key groups and their roles in technology adoption and training.
- Review suggested industry 4.0 technical skills to cover in on-boarding training.
Workforce development insights
- When considering your plant’s workforce, look at the work experience, skill level and ability to adopt new technology.
- Each generation in the workforce approaches digital transformation, artificial intelligence and automation differently.
The introduction of modern technologies into manufacturing is an ongoing and continuous process. However, the rate at which innovative technologies are being adopted and how quickly things are changing is unparalleled. We have all learned, especially during the “pandemic years,” that working groups are more dynamic yet chaotic because of the balance of employees working on-site versus remotely.
Due to societal and workplace changes, an employee working their entire career for one company is now a rarity. It is generally accepted that someone will have several different jobs during a career.
This premise readily establishes the importance of teamwork and the working dynamic between management and the unique experience groups. Figure 1 portrays the interplay between three key groups: current manufacturing executives and other decision-makers, the existing workforce of manufacturing professionals and the incoming workforce comprising millennials (born between 1981 and 1996) and Generation Z (born between 1997 and 2012).
The first group encompasses decision-makers or executives — individuals with managerial roles in the manufacturing sector. These stakeholders typically exercise final authority over manufacturing technology adoption, given their responsibility for financial metrics such as profit and loss. Furthermore, they steer the direction of the firm’s projects, deciding which areas merit exploration. This group also significantly influences retention and hiring strategies for their facilities, determining employees’ scope of assignments, their objectives and the workforce composition and size.
The second group, the existing workforce, consists of manufacturing professionals with several decades of experience within their environment. They typically have a comprehensive understanding of manufacturing processes and a unique conception of their firm’s standards. Statistically, they likely spent most of their careers with the same firm, which engenders substantial “tribal knowledge” about inputs leading to desirable outcomes regarding products, equipment and overall operational efficiency. While this group might not be as acquainted with the latest manufacturing technology, especially concerning machine learning and artificial intelligence (AI), they are well equipped to identify where connectivity and remote monitoring solutions will deliver the most value.
The third and final group of interest, the incoming workforce, comprises younger manufacturing professionals who often have limited or no experience in their specific fields. While less familiar with the specific operations and equipment that contribute to their firm’s success, they are more exposed to the state-of-the-art technology available to manufacturing firms. Their education makes them more likely to have encountered collaborative robotics, machine learning algorithms and AI tools. This group plays a pivotal role as the inheritors of current manufacturing processes, which are typically well integrated into a firm’s value stream.
Interaction for success
For managers of any level, it is critical to be stewards of an organizational structure that provides a consistent — but flexible when needed — process for individuals to interact. They must possess the following attributes:
Being able to work within a team.
Listening to other viewpoints and disciplines when solving problems.
Identifying process bottlenecks with both machinery and human workflow. Much of this entails pinpointing areas where individuals can be cross-trained.
Ensuring information is accessible and up-to-date. If a new team member is introduced, they can quickly learn the basics of a team’s function.
All this work takes time and there is always the danger of “paralysis by analysis.” But using standardized procedures and checklists can often lay the foundation for a sustainable work culture.
This leads to the importance of the interaction between the second and third groups of interest: the existing workforce and the incoming workforce. Having people work in teams is always going to be relevant. The incoming workforce has more exposure to machine learning and AI tools but lacks the wealth of experience of their veteran counterparts. It’s crucial for the existing workforce to share their understanding of current manufacturing processes with these newcomers. Everyone in this situation can teach and learn.
Manufacturing executives, interacting with both groups, guide the firm’s technology adoption and often have the final say on investments in industry 4.0 technologies. They need to acknowledge the importance of retaining long-term talent and ensuring sufficient knowledge transfer between the existing and incoming workforces.
The Motion Automation Intelligence team has been to manufacturing plants and heard managers say, “We used to have much more training, but our turnover is so high, we just do the minimum!” This approach is a self-fulfilling prophecy, invariably leading to a poor long-term outcome.
Many organizations actively produce training material in smaller blocks and online, video and in-person sessions. They focus on providing that work to a dedicated project team. Interaction skills are more crucial here than ever.
The Motion Automation Intelligence team does a great deal of onboarding training on technical skills that we consider fundamental to customer interaction. The group often calls this “knowledge at the point of sale.” The following skills pertain specifically to an automation solutions provider:
A clear grasp of how machine control is accomplished. Understanding how electrical panels with relays were the basics. Understanding why programmable logic controllers (PLCs) are so widespread now and how recent technologies and platforms can coexist with older equipment.
Industrial connectivity and visualization: tying machines, different lines and infrastructure together.
Understanding communications at the serial level (RS-232, RS-485), the intermediate bus technologies (e.g., Profibus, DeviceNet, Interbus-S, CC-Link, Data Highway Plus) and industrial Ethernet, which is only growing.
Understanding how PLCs, human-machine interface (HMI), supervisory control and data acquisition (SCADA) and input/output (I/O) are often tied together via Ethernet, as the information technology and operational technology worlds converge. This means knowing the important differences between unmanaged and managed switches, copper versus fiber, etc.
Newer control technologies such as CODESYS are especially important for the experienced groups not to dismiss.
Combining unique workforce skills
Separate groups must come together and define how to assemble the different puzzle pieces of automation for a project. For example:
What is at the actuating or “work” end? Knowing when to employ hydraulics, pneumatics, electric actuators, mechanical devices such as ball screws and servo motors has always been a basic need.
Where robotics work with these existing technologies. Understanding the differences between robot types continues to evolve.
Sensors and remote types of I/O — always a factor.
Safety, a critical consideration as humans interact closely with robots and machines.
Network security and devices to create “defense in-depth,” crucial for all the Ethernet connectivity and the omnipresent danger of hackers and saboteurs.
Edge computing, taking over some of the functions previously done with a PLC, traditional HMI or SCADA.
Cloud technologies, which have changed the landscape and provide new opportunities and challenges for envisioning architectures and security. These include remote-access virtual private networks, always-on data collection and virtual dashboards.
A single person is rarely an expert in all these technologies, so teamwork is more important than ever. As the three groups interact, certain interaction points should be emphasized as companies adopt emerging industry 4.0 technologies. Machine learning and AI tools’ effectiveness hinges on the quality of input data used to generate actionable outputs.
Besides automating data collection and analysis, similar challenges arise with physical types of automation that have recently emerged in the manufacturing technology scene. As firms increasingly adopt collaborative robotic technologies and other related robotic guidance systems, understanding current manufacturing processes is crucial for their integration. If these existing manufacturing processes’ nuances are overlooked, the implementation of emerging robotic technologies can easily derail. Similarly, just as machine learning and AI tools struggle without quality input data, robotic implementations can fail with insufficient data on high-value projects suited to these technologies.
In summary, these are unique times regarding technological advancement. Although people will change jobs more than previous generations, it is proven that good, relevant training is still a priority. Commonly, someone will start at a company in an entry-level position, leave for other jobs to gain experience and different perspectives and then return to offer even more to their original employer. It is for the good of society if everyone “raises their game” because we are all interconnected.
A clearly defined company culture will always be paramount. It means valuing all employees and providing an environment to succeed while encouraging teamwork. How we treat our most important resources — our employees — will be a guiding principle regardless of technological advances.