Komarov Artem clarified that 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, said Artem Komarov.