OM in the News: Manufacturing Jobs are Looking Very Different

Digital transformation and Industry 4.0 are changing manufacturing, but the fact is that skilled operations talent is increasingly harder to come by. With projections that 2.4 million manufacturing jobs will be unfilled by 2028, the question becomes: What talent and skills do companies need in order to succeed in the factory of the future? Industry Week (Aug. 25, 2021) looks at four manufacturing jobs and how they are expected to evolve. 

Production Planners will shift from managing shop floor issues to more proactive roles in which they analyze data insights, manage exceptions and identify opportunities for continuous improvement. They will move from using manual processes for monitoring inventory to using predictive analytics and “digital twins” (virtual representation of a part or a process) to create optimized production schedules and proactively manage inventory issues. And they will need skills in lean and six sigma, data analysis and visualization.

Industrial Engineers will increasingly use digital twins and other cyber-physical systems, in addition to other methods of automation, to create greater connectivity between manufacturing processes and shop floor operations. They will need skills in the areas of design for manufacturability, data science, python and R  programing languages,  co-bots, IoT sensors, digital twins and wearables.

Machine Operators. Today’s operators tend to specialize in one machine or product line and rely on personal judgment in overseeing machines and processes, leaving room for human error. In the future, operators will use digital twins and AI to proactively identify and solve issues. They will be trained as generalists who can work across machines and product lines.

Quality Analysts. Today’s quality experts are often making changes to standards in reaction to customer complaints, bad yields, or defective products. In the future, they will be able to monitor processes in real time, predict quality issues before they occur, and quickly trace and diagnose any issues through the use of digital twins, advanced analytics and the ability to embed intelligence quality controls. This will require an understanding of big data, data science, and machine learning.

But beyond the clear need for a much higher level of digital acumen, there is also a critical need for human skills that machines cannot replicate such as conceptual thinking, decision-making, problem-solving, and innovation.

Classroom discussion questions:

  1. How many of your students will consider manufacturing jobs? Why?
  2. Explain the concept of a “digital twin.”

OM in the News: The Fourth Industrial Revolution–Industry 4.0

A recent IndustryWeek survey (Nov. 6, 2018) found that manufacturers are having trouble joining the Fourth Industrial Revolution, called Industry 4.0. And the World Economic Forum (WEF) found that 7 out of 10 manufacturers fail in pushing initiatives in big data analytics, A.I., and additive manufacturing.

But there is hope, the Forum asserts. They scoured the planet and after vetting 1,000 manufacturers, selected 9 “lighthouses” (listed below) with a solid Industry 4.0 strategy. “These pioneers have created factories that have 20-50% higher performance and create a competitive edge,” says a McKinsey exec. “They have agile teams with analytics, IoT and software development expertise that are rapidly innovating.” Industry 4.0 is expected to deliver productivity gains over $3.7 trillion.

Bayer Biopharmaceutical: Italy. Most companies use less than 1% of the data they generate. Bayer makes the most of its data, leading to a 25% drop in maintenance costs and while gaining 30-40% in operational efficiency.

Bosch Automotive: China. Bosch uses data analytics to deeply understand and eliminate output losses, simulate and optimize process settings, and predict machine interruptions before they occur.

Haier: China. Use of AI facilitates a “user-centric mass customization model” with electronic products made on-demand. Maintenance needs are predicted before incurring downtime via AI.

Johnson & Johnson: Ireland. This hip and knee joint factory implements IoT, leading to a 10% reduction in operating costs and 5% drop in machine downtime.

Phoenix Contact: Germany. The electronics manufacturer relies heavily on customer-specific clones to cut production time for repairs or replacements by 30%.

P&G: Czech Republic. Production lines, in a plant built in 1875, seamlessly change the product being manufactured with a push of a button, an innovation that reduced costs by 20% and upped output by 160%!

Schneider Electric: France. Sharing of best practices across its multinational force allows each site to reap the benefits of the others, saving 10% on energy and 30% on maintenance.

Siemens: China. Leveraging augmented reality to create 3D simulations, Siemens has optimized its production lines with reduced cycle time and 300% jump in output.

Fast Radius: U.S. The lone U.S. company uses real-time analytics and globally positioned distribution 3D printing farms to maintain rapid turnaround times to deliver prototypes and custom parts.

Classroom discussion questions:

  1. What is Industry 4.0?
  2. What do these 9 firms seem to have in common?