Business process reengineering started in the 1990s when technologies like enterprise resource planning (ERP) were boosted by the latest rage at the time–a burgeoning technology known as the internet.
However, in spite of the big promises, these technologies were quite limited in how they could transform the manufacturing industry. The more popular ERP systems made processes too rigid, which compelled manufacturers to rely more on methodologies instead of technologies.
As a result, reengineering technologies remained limited to transactional and communications-based solutions.
Thanks to the rise of artificial intelligence (AI), this might be changing.
AI in Manufacturing
Whilst previous technologies were great for data capture and transfer across an organisation, AI-based technologies are excellent for quicker, faster, and more automated decision-making.
With machine learning (ML), AI can digest large datasets and use them to come up with predictions. These predictions then enable better business decisions, which could make production planning and control more efficient.
Additionally, image recognition could also make inspections easier. AI can also enable autonomous operations and the generation of new content.
Even within the realm of automation, robotic process automation is being replaced with ML-driven intelligent process automation.
The issue is, with AI powering automation, manufacturers need to re-evaluate their processes, especially in the case of partial automation.
That means the workforce would also need to be trained to use the technology. Unfortunately, US manufacturers have discovered that their workers may not have the skills to adopt robotics and automation easily.
Bridging the Technology Skill Gap
According to this story, there are five ways in which manufacturers can train and upskill their workforce so they can keep up with automation technology.
Create Training Programmes
Training is a great way of not only improving worker abilities but also keeping them engaged and invested in the business. Process training, especially, can be useful in providing workers with hands-on experience.
Whether it is a new process or new software, this can be effective in introducing workers to newer ways of working.
Start Apprenticeship Programmes
The problem with the workforce in manufacturing is that older and more experienced workers are often not comfortable working with new technology. However, they have a deep understanding of the processes involved.
To ensure that this knowledge is not lost, they could be asked to mentor newer workers, which would help the younger workforce learn faster. What’s more, the opportunity can be used to refine specific skills required by the business in the future.
And, the knowledge flows both ways, where the older workers can learn to be comfortable with newer technologies with the help of younger workers.
Use Technology to Train
Training by reading books and manuals is not engaging and doesn’t inspire workers to learn. However, technology can also be used to upskill the workforce in a manner that is as comprehensive as it is safe.
Augmented reality (AR) and virtual reality (VR) can be both harnessed to teach valuable skills to workers before they are put in front of actual machines.
Follow Lean Manufacturing Principles
Lean manufacturing is a way of increasing productivity whilst reducing waste. Training the workforce in these principles can help with improving processes. Investing in processes such as the Gemba Walk (explained in detail by Ease.io, the digital audit and inspection platform for manufacturers) and Six Sigma can help businesses achieve lean status.
Use Local Institutions for Training
Local educational and economic development institutions can be a valuable resource for training one’s workforce. These can be especially useful for small and medium manufacturing businesses.
By investing in upskilling its workforce, an organisation can optimise its productivity whilst also ensuring workers are happy and aren’t intimidated by new technologies.
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Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.