Leveraging Artificial Intelligence in Operations Management

BY: CHUCK WERNER

Owners and leaders of small to midsize businesses frequently find it challenging to spend enough time working ON their businesses because they too often find themselves working IN the business. Until now, few tools were available to help managers find the time to strategize and pursue business improvements. Artificial Intelligence (AI) can give the gift of time to manufacturing teams everywhere and make running a business easier. Learn about four key AI applications in manufacturing below:

1. Machine Monitoring/Upkeep
   Overview: Many manufacturers have machines that can shut down manufacturing operations in the event of mechanical failure. The tens of thousands of dollars required to repair such machines, plus the loss of productivity during a breakdown, can hamper a company’s ability to meet customers’ expectations. Even if they have a standing agreement with another company to provide the process step as an outside service, the transportation and additional costs can affect the company’s bottom line.
   
   Impact: AI-powered predictive maintenance relies on sensors and machine learning algorithms to analyze data from machinery. Additionally, AI provides superior analytical capability to determine machine conditions and tirelessly examine data to recognize changing performance. This data-driven approach minimizes unplanned downtimes, significantly reduces maintenance costs, and improves overall operational efficiency. According to industry reports, implementing a real-time predictive maintenance program can reduce maintenance costs by up to 30% and cut downtime by 50%.
   
   Availability: With the increasing affordability of IoT devices and the growing availability of machine data, real-time machine monitoring is a “now” proposition. Its ability to integrate with existing systems and provide real-time insights makes it an essential tool for manufacturers seeking to stay competitive. The important thing for company leadership is to understand which machines are critical enough to require investment. Where redundancies and additional capacity exists the return on investment may depend solely on reducing repair costs or spare parts inventory dollars.
    
2. Quality Control and Inspection
   Overview: AI in quality control and inspection involves using machine vision and deep learning algorithms to detect defects, inconsistencies, or anomalies in products during the manufacturing process. But perhaps the greatest advantage is that, once trained, the AI-driven inspection is continuous— it never gets tired, distracted, or bored, making the 100% inspection much more than 80% effective.
   
   Impact: Traditionally, quality control has been a labor-intensive process prone to human error. AI automates this task with high precision, ensuring that only products meeting the highest standards reach the market. AI-driven quality control enhances product reliability and reduces waste and rework, contributing to cost savings and higher customer satisfaction.
   
   Availability: The rise of high-resolution cameras, advanced imaging technology, and more sophisticated AI algorithms is driving the rapid adoption of AI in quality inspection. Training of AI vision systems can be a painful and expensive experience, but as AI capability increases and cameras become less expensive, applications will increase. Eventually, AI will be used to create the defect samples to reduce the implementation time and cost. When it comes to quality control that ensures customer satisfaction, the technology is ready to apply and is becoming a great investment.
    
3. Production Planning and Scheduling
   Overview: Planning and scheduling production requires complex decision-making processes, considering variables like machine availability, labor resources, material supply, skillsets, and often, customer patience. Frequently, the company relies on an individual who seems to be able to see all the moving pieces in their head. However, even if they can today, continued business growth will result in too much complexity for one person to juggle.
   
   Impact: In traditional manufacturing settings, production planning is often a manual and time-consuming process. AI-driven systems can generate optimized production schedules that maximize resource utilization, minimize downtime, and ensure timely delivery of products. This improves operational efficiency and provides greater flexibility to adapt to changes in demand or unforeseen disruptions. Additionally, that subject matter expert will not need to perform the busy work of scheduling but will instead be able to focus on areas of concern for the business.
   
   Availability: As manufacturers face increasing pressure to meet tight deadlines and deliver customized products, AI-driven production planning and scheduling tools are becoming indispensable. The shift towards smart factories and Industry 4.0 is further accelerating the adoption of these AI applications. There are currently many systems available that can assist in setting a schedule and monitor adherence to it, providing trending information that helps the team stay ahead of problems.
    
4. Trend Analysis/Process Improvement
   Overview: AI-powered technologies have many capabilities that can drive operational efficiencies. For example, they excel at data collection and entry, data processing, machine learning and analysis, pattern recognition, and predictive modeling. All of these are time-consuming functions that prevent team members at all levels of the business from working on critical issues or finding better ways to perform their tasks.
   
   Impact: In addition to relieving the time-consuming data entry tasks and providing trending analysis, AI can also discover trends and correlations in the data. While correlations are NOT causation; they are often enough to help a dedicated process improvement individual to get closer to causal factors and root causes more quickly. Trending analysis, as noted earlier, provides an “early warning system” for the organization allowing them to take a proactive approach. 
   
   Availability: AI and machine learning technologies are readily used in larger corporate environments and are becoming more accessible to businesses of any size. Three challenges to leveraging these affordable and powerful AI and machine learning technologies include 1. identifying the information needed to successfully run the business (i.e. building the data collection plan); 2. ensuring that the data is entered accurately and per the plan/ and 3. having people who are trained in the technologies and able to manipulate the data and reports to provide useful reports and insights to decision makers. Automation of data collection is a best practice to ensure good data. Education regarding these technologies is critical to success. As adoption of these technologies grows, businesses should familiarize themselves with applications and pricing to stay competitive in today’s industry. 

AI presents myriad opportunities to improve the efficiency and effectiveness of processes and the quality of outputs and is becoming more accessible as time goes on. MMTC’s consulting services or Technology Opportunity Assessments can help small and midsize manufacturers identify potential uses for AI technology, explore funding assistance, and successfully implement new technologies. Contact us today and our experienced Business Solutions Managers will connect you with the resources, tools, and support for an even brighter manufacturing future. 
 

MEET OUR EXPERT: Chuck Werner, Manager Operational Excellence/Lean Six Sigma Black Belt
Chuck has been a member of the MMTC team since 2016. His areas of expertise include Industry 4.0, Lean, Six Sigma, and Quality. Chuck has devoted many years to practicing Six Sigma methods, ultimately earning a Six Sigma Master Black Belt in 2011. He is passionate about helping small and medium-sized manufacturers become more prosperous using various tools and methods gathered from more than 30 years of experience in manufacturing.

Since 1991, the Michigan Manufacturing Technology Center has assisted Michigan’s small and medium-sized businesses to successfully compete and grow. Through personalized services designed to meet the needs of clients, we develop more effective business leaders, drive product and process innovation, promote company-wide operational excellence and foster creative strategies for business growth and greater profitability. Find us at www.the-center.org.