In manufacturing’s changing times, management style matters

In the future, successful managers in manufacturing will be judged by their ability to prepare employees to master technology and respond to both good and bad analytical results. Nuthawut Somsuk/iStock/Getty Images Plus

Manufacturing is currently in one of the most dynamic periods in its history. Materials, machinery, processes, and information technologies are changing constantly. As electric vehicles become more prevalent, automotive body structures are being redesigned to secure and protect batteries. Household appliances are becoming more energy efficient and are integrating smart technologies. Simulation tools are commonly used to design products, identify solutions, and test the results of design. While these developments present a great opportunity for manufacturers, they also involve great risk and can cause much frustration.

The advancement and integration of analytical technologies into all aspects of manufacturing also offer both opportunity and risk, but many manufacturers remain unable to grasp their capabilities. The lack of a common naming convention certainly doesn’t help matters. Is it smart manufacturing? The Industrial Internet of Things? Machine 2 Machine? The 4th Industrial Revolution?

And often, it seems there is more hype than substance. Technologists and business leaders are issuing alarms about the serious risks involved with artificial intelligence, with some even warning of human extinction. I doubt that a live reenactment of “The Terminator” is in our immediate future. For now, Sarah Connor is safe.

Data technologies are, by their nature, regressive. Analysis and recommendations are founded solely on past events. Data is also biased toward prior decisions and activities, and it becomes stale and obsolete. Computers can’t replace the forward-thinking ideas of knowledgeable and creative employees. Knowledgeable employees also can notice biases in analysis and recommend actions to eliminate that bias.

But people have died already from overconfidence in technology and neglect in caring for technology components—consider the two 737 MAX aircraft crashes in 2018 and 2019, and the BP Texas City refinery explosion in 2005. Poor human decisions in design and maintenance led to catastrophic failure. These cases are evidence that technology is not a neutral object. Our technologies often reflect and amplify our own strengths and weaknesses.

If you look behind the curtain, smart manufacturing is just an advanced form of technology-enabled statistical process control. If we are to master it, we first must master our industry. Many variables and processes determine how successful we’ll be in forming a sheet metal blank into a quality component. Some of these include the mechanical properties and blank dimensions, coatings and treatments, the quality of sheared surfaces, the lubricant used, how the lubricant is applied, the shape and status of tooling surfaces, the accuracy and precision of the die design, punch speed, press tonnage, calibration, and balanced state of the press and other equipment.

Successful technology development depends on the contribution of subject matter experts, including manufacturing engineers, metallurgists, design engineers, equipment operators, maintenance and reliability employees, logistics managers, and quality inspectors. Their expertise must be what seeds smart manufacturing data and analysis. SMEs also are your most reliable resource to identify faulty analysis. This makes it critically important to develop and maintain the knowledge of SMEs in both their manufacturing area and in the products of analysis.

Develop and Support Your Employees Though Change

Network and computing technologies make it easier to identify and react to problems quickly. But how do you integrate all of this with your workforce? Mainly, you must support employees through change if new technologies are to be productive and nondestructive.

My dad’s experience is a good example. Dad left high school to join the Navy at the end of the Korean War. He served his time on the Atlantic coast as a sonarman and found his interest in electronics. After the Navy, he apprenticed at New York Shipyard on the N.S. Savannah. The Savannah was a project supported by President Eisenhower to promote nuclear propulsion in merchant ships. New York Ship taught him to be an electrician.

After New York Ship, he moved to a polypropylene plant owned by a global oil company, working his way up to maintenance foreman. An old-school company man, he seemed happy and was well respected for his skill and dedication.

Dad specialized in maintaining and calibrating analog instrumentation during the 1960s and 1970s. In 1977, he was offered a promotion and transfer to a large refinery and chemical plant outside of New Orleans.

Then, during the 1980s, the world started to turn digital. While in college, I noticed my dad was still happy, but became increasingly frustrated. During a conversation, Dad told me that he was frustrated with the pace of digital technologies and its effect on him. Old pen and paper reports moved to spreadsheets. Instrumentation became digital and more remotely operated.

When his management noticed his struggles, they simply told him to learn how to use new technology. While he was proud of his talent and contribution, he was obviously very frustrated that his company did not support his need for further training. He was eventually retired because of his struggles to keep up.

Today’s changes in manufacturing are even more disruptive and broader in scope than the migration from analog to digital in the ‘80s and ‘90s. Both experienced and new employees need training and direction to develop and maintain the breadth of skills necessary in modern manufacturing. Success and safety in tomorrow’s manufacturing plants will be decided by how well we prepare employees to master technology and respond to both good and bad analytical results.

Redefine Leadership

Successful manufacturing requires talented leaders who can see the opportunities of change but also understand the impact of change on the workforce and support employees through it. Effective leaders know how to guide both new technology and employees to a goal and accomplish real results.

Today’s younger workforce also expects more from management, especially after COVID. Today’s employees won’t stay to work for the posers and opportunists that frequently occupy management positions. Expectations include:

• Effective and productive communication.
• Alignment with company vision and values.
• Encouragement.
• Decisiveness.
• Meaningful and timely feedback.
• Ethical behavior.
• Accountability.

We’ve always wanted these behaviors from our leaders, but in today’s tight environment for employees, they aren’t optional anymore. Some of the labor shortages in manufacturing today could well stem from the management abuses of the past. Parents and grandparents shared stories of difficult and dirty workplaces, discouraging their children from pursuing manufacturing jobs.

We need to do better. Seniority-based promotion isn’t sustainable in today’s world. Promotions into leadership positions must be based on knowledge, skill, production performance, and interpersonal skills.

Define Your Ethics and Be Transparent

Implementation of smart manufacturing should begin with the whole organization’s understanding of management’s ethics regarding this technology. Will you monitor employees, and to what degree? How will you guarantee employee and plant safety? How will you prevent data manipulation, or punish it? Will you allow employee intervention in an automated process, and how will you manage it?

Both management’s ethics and the source and mathematics behind analysis must be transparent to everyone in the company. If machine learning is involved, everyone must know how analysis and recommendations are created. Otherwise, algorithms might find correlations among variables that are improper or destructive to the quality of the analysis.

Effective Leadership + Knowledgeable Employees = Success

Smart manufacturing should be the product of smart implementation. This means that risks and opportunities are fully researched. Opportunities should be implemented within your scope. Opportunities that you can’t afford right now should be managed and controlled in a disciplined manner. Risks must be understood, explained, and managed.

Despite the rhetoric, smart manufacturing demands a highly skilled and knowledgeable workforce. Data scientists know data, but your plant floor employees know what the data means and what should be included in a sample population. If analysis is wrong, a skilled employee who understands how decisions will impact plant and employee safety is your best defense against poor results.