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Home / Welcome to the Next Decade: Metalworking in Industry 4.0

Welcome to the Next Decade: Metalworking in Industry 4.0

During the next ten years, more fabricators will compete with sophisticated, connected networks that apply artificial intelligence to manage data that reduces their cycle times in design to manufacturing to delivery.

DataProphet offers a comprehensive Artificial Intelligence Suite to improve production quality and reduce defects for Industry 4.0. During the next ten years, the competitive use of sophisticated, connected networks that apply varying degrees of artificial intelligence to manage big data will help metal fabricators increase their process speed in design concept to order input to manufacturing and delivery. AI and human learning will impact most aspects of manufacturing, resulting in improved profits, inventory levels and cash flow.
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During the next ten years, watch for the operations of all metal fabricators – regardless of size – to evolve and compete by building sophisticated, connected networks that help them increase their process speed in design concept to order input to manufacturing and delivery by using varying degrees of artificial intelligence (AI) in the management of big data. The competitive use of AI to effectively organize, analyze and apply enormous volumes of information for making faster and better decisions will, in turn, drive the emergence of smart factories, expand the applications of autonomous robots, and transform the way we all live and work in an Internet of Things (IoT) environment. “AI and other forms of technology are transforming manufacturing as we know it. From reevaluating sourcing and enabling robots to predictive maintenance and shortened design times, AI offers up vast potential. AI and human learning will impact most aspects of manufacturing, resulting in improved profits, inventory levels and cash flow,” predicted Lisa Anderson, MBA, CSCP, CLTD, the president of LMA Consulting Group Inc. (Claremont, CA). “Our manufacturing clients have really embraced the power of AI during the last year. From improved forecast accuracy that affects inventory levels, to working more openly with changing customer needs and the overall customer experience, they are already seeing the effects of using this data.” 1

However, learning how to navigate this perfect storm for manufacturing success doesn’t come easy. “Companies still need to be smart. This takes work, sharp management and a strong team to be successful,” cautioned Anderson. “By integrating AI with tried-and-true sales, inventory and operations planning techniques  and taking advantage of predictive analytics and other human learning technologies in conjunction with ERP systems, manufacturers can become better at forecasting and exceeding customer expectations. In fact, for every one percent improvement in forecast accuracy, there can be a seven percent improvement in inventory levels and therefore cash flow.” 1 So competing with big data can be incredibly beneficial, but the secret to getting the most out of it isn’t the quantity, but the quality.

Big Data, or Just Data?
Manufacturers have come to realize that the secret to getting the most out of boundless volumes of information isn’t quantity, but quality.

As automation changes the way factories operate, some manufacturers are already training their machinists in programming and robotics to get a taste of coding. For example, the machinists at Marlin Steel Wire Products LLC (Baltimore, MD) develop code for the $2 million worth of robots used in their manufacturing of wire baskets that replaced several workers who physically created parts. Other employees use collaborative software to interact with customers on real-time design changes, helping the shop manufacture higher-quality steel products, charge more for them and create unique intellectual property. “We’re not going to beat the competition because we are charging lower prices,” explained Drew Greenblatt, the chief executive officer of the company. “We are going to beat the competition because of our technology. These factory workers are turning into coders to exploit technologies.” 2

“The next generation of manufacturing work is all about generating, keeping track, and getting data where it needs to go to keep production processes in control and to capture new opportunities,” said Nicole Radziwill, an associate professor of data science and production systems at James Madison University (Harrisonburg, VA). Manufacturing and repair firm Radwell International Inc. (Willingboro, NJ) identified workers with an aptitude for learning and decent knowledge of processes and systems and trained them in skills such as programming on Visual Basic to build software tools to handle tasks like purchasing. Radwell IT staff who learned Python, a programming language used widely in artificial intelligence and data science, built an AI system to sort incoming parts. The system helps recognize parts based on rough contours, differentiating a circuit breaker from a motor. The staff is currently developing a machine-vision-based AI system to recognize parts. “We are automating processes through technology, whether it’s AI or system settings like ordering products,” noted John Janthor, the vice president of information technology at Radwell.2

References
1. “Manufacturing Expert Sees Impacts of AI on Manufacturing Profit, Inventory Levels and Cash,” Lisa Anderson, LMA Consulting Group, Inc., September 9, 2019, LMA-ConsultingGroup.com.
2. “Factory Workers Become Coders,” Agam Shah, The Wall Street Journal, May 20, 2019, www.wsj.com.

Welcome to the next decade of metalworking, where the shop floor operates in an Industry 4.0 environment and the competitive edge lies in automation and the smarter use of data:

How Pre-Emptive Replaces Real-Time
Because real-time is too late, the comprehensive Artificial Intelligence Suite from DataProphet can achieve real impact with pre-emptive actions to improve production quality and reduce defects for Industry 4.0.

Electro-Spindle Monitors Cutting Processes in Real-Time
The e-SPINDLE from PCI / Absolute Machine Tools integrates sensors and actuators to monitor cutting processes and adjust parameters to optimize tool life and part quality.

Intelligent Toolholder Controls the Cutting Process in Real-Time
The smart iTENDO hydraulic expansion toolholder from SCHUNK enables real-time process monitoring and control of geometry and performance data directly in the tool.

Automated Adaptive Milling
Automated adaptive blade milling from Liechti Engineering measures the workpiece in the machine and CAM software generates and optimizes a tool path that eliminates human error, optimizes productivity and ensures the highest quality result.

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