Manufacturing is experiencing an unprecedented disruption. Non-essential manufacturers are faced with furloughs as they pause operations and manufacturers of essential products are adapting to operating with fewer people. While the lasting impact of COVID-19 remains to be seen, the long-standing fact remains that there’s a wide disparity between the number of people entering the field of manufacturing and the needs of the industry.
Estimates put the manufacturing labor shortage at 2.4 million by 2028, according to Deloitte, and we can’t assume this gap will be solved by a sudden influx of employees after COVID-19 restrictions are eased. The number of retirees continues to increase as the working population ages; meaning there will still be a lack of sufficient qualified applicants to replace them. Manufacturers must prepare for the long-term reality they are facing – operating with fewer people on the floor and insulating themselves from the loss of domain knowledge.
Manage Knowledge And Mitigate Risk
One of the biggest risks manufacturers face in the coming years is the loss of domain knowledge with the generation who are retiring now, or in the near future. This encompasses years of experience that likely lives only in employees’ memories. Process settings or maintenance secrets aren’t written down – meaning they won’t be transferred to future employees. That’s an enormous threat for manufacturers.
The first step is to translate that domain knowledge into intellectual property by systemizing it and putting it into business workflows and processes. This requires a data infrastructure that captures and analyzes the knowledge, and can provide intelligence into what works and what doesn’t. Analyzing everything in your production process significantly reduces the risk of that knowledge loss.
Machine learning technologies can analyze data from past production runs to identify your most profitable and most efficient runs, as well as your least profitable and least efficient runs, along with the process settings that contributed to each. These technologies can then recommend optimal settings to replicate your best performing runs more consistently.
This will also drastically improve your training when you’re actually hiring people. Instead of learning by observing a person at work – which won’t be an option once those retirees have left – new hires can actually invest in learning best practices from your systems, processes and workflows.
Prepare to Operate With Fewer People
The impact of COVID-19 has accelerated the need to operate with fewer people on the floor and highlighted the critical importance of digital transformation solutions, including remote monitoring and applied analytics. Operating your factory with a pared-down workforce must be part of your long-term plans. The best way to do that is by streamlining your existing processes and increasing data transparency.
One of the core lean principles is to remove non-value added tasks. But a tremendous amount of engineers spend valuable time looking for information in different systems and then putting it in Excel spreadsheets. We’ve seen numbers that say engineers spend 30% to 70% of their time looking for information. Investing in a centralized data architecture – such as an OPC server, data historian and/or SQL database – will help combat this problem.
The second is by implementing collaborative intelligent applications. Machine learning-based platforms that work with employees inject significant efficiency gains. Just as machine learning models help doctors identify MRI scans that require attention, manufacturing machine learning systems can sort through millions of data points and highlight the most important and help you devise a course of action.
Machine learning can be used to develop models that provide manufacturers visibility into production processes, inline and offline quality and help rapidly identify the root cause of a failure. Machine learning lets you identify the critical indicators in terms of process metrics that flagged a production issue – specific conditions right before the quality failure, like a drop in speed or a temperature fluctuation, can be isolated and linked to that failure and help identify the likely amount of bad product much more accurately. This visibility means engineers and factory floor personnel spend less time manually investigating and correcting production problems.
Create Training Programs
How do you ensure that your existing employees not only maintain historical knowledge but improve their own skills? How do you make sure new employees are ramped up quickly and are productive as they can be, as quickly as possible? By offering in-house training programs.
In some European countries, and this is something we see spreading to the U.S., apprenticeship programs are helping to combat the skills shortage. Paid training positions can be an alternative to a four-year college degree, and can offer wonderful career paths and growth.
For existing employees, it’s important for organizations to offer opportunities for upskilling internally. Even with younger or mid-career employees, making more with fewer people still applies. Upskilling programs will help them better prepare for the future because they’ll learn highly-transferable skills. They can learn data analysis tools or how to manage and maintain automation equipment – the kinds of knowledge that are part of the transformation all manufacturers are undergoing.
Manufacturing also has a perception problem. There’s an information gap: people aren’t aware these interesting careers exist, are well paid, and that the industry is in need of workers. Improving awareness of the opportunities available will help companies attract the talent they need, while helping to revitalize and grow economies outside of the major magnet cities – where the cost of living has increased to the extent that younger workers can have a tough time getting a foothold. The solution is for manufacturing to rebrand as an interesting, stable and well-paid career.
The global economic circumstances triggered by COVID-19 have presented an intensely challenging manufacturing landscape, which is unlikely to abate soon. They have also highlighted various shortcomings of manufacturers’ processes. Those who have already implemented intelligent solutions were prepared for remote monitoring and operating with less people on the factory floor.
For any industry that needs to prepare for an economic downturn, intelligent solutions enable more efficient operations which lead to increased contribution margins. Taking action now will not only increase productivity and competitiveness, but make your factory a magnet for the skilled talent you need. Assess your workforce needs now, offer the training and advancement employees want and determine whether your current workflows, processes, and platforms are advantageously positioned as collaborative tools. Those three steps will safeguard your company against fluctuations in labor availability and position you for continued success.
This article was written by Willem Sundblad from Forbes and was legally licensed through the NewsCred publisher network. Please direct all licensing questions to firstname.lastname@example.org.