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Manufacturing Workforce Trends: The Impact of Technology and AI

The manufacturing industry is witnessing a transformation due to advancements in technology and artificial intelligence (AI). These changes are reshaping the workforce, enhancing operational efficiency, and driving the transition from Industry 3.0 to Industry 4.0 and beyond. Staying informed about these manufacturing workforce trends is crucial for remaining competitive and preparing their factories for the future.

Shift from Manual Labor to Skilled Labor

One of the most notable trends in the manufacturing workforce is the shift from manual labor to skilled labor. As factories adopt more sophisticated machinery and automation technologies, the demand for manual labor decreases while the need for skilled technicians, engineers, and IT professionals increases. Apprenticeship programs are in high demand as some industries face a possible 1.9 million worker shortfall by 2033. Investing in training programs to upskill current employees and attract new talent with the necessary technical expertise is essential for modern manufacturing plants. The integration of robotics, AI, and advanced production monitoring systems has driven this shift. A higher standard of workforce is need to manage and maintaining these technologies.

For example, predictive maintenance systems can anticipate equipment failures before they occur, reducing downtime and improving efficiency. However, these systems require skilled workers who can interpret data, understand AI algorithms, and perform complex troubleshooting. While it may be tempting to jump to AI algorithms as the next step, a data collection system needs to be in place first. Many manufacturing plants still collect data through manual reporting. Production counts are recorded on a clipboard before handing off the task to an unfortunate intern to enter into Excel. Conducting complex analysis on last week’s Excel spreadsheets is like the local meteorologist telling you what the high temperature was last Thursday. Outdated and ultimately useless. Proactive decisions can’t be made without real-time data. These interpretations shouldn’t need a PhD to understand either.

H&T Waterbury Moves to Condition-Based Maintenance

Mingo Smart Factory and Fiix created a native integration to provide insight and create communication between operations and maintenance. H&T Waterbury, the largest battery component manufacturer in the world, is one of those companies taking advantage. The integration works by transferring information between the two systems using vibration and temperature sensors. Data is collect by Mingo sensors and transmitted the manufacturing dashboard to understand trends, reporting, and analysis of data. The maintenance team schedules maintenance activities, tracks inventory, and maintains workflow in Fiix.

Emphasis on Data-Driven Decision Making

The advent of real-time data and analytics has transformed the way decisions are made on the factory floor. Manufacturing executives and plant managers now have access to a wealth of information that allows them to make more informed, data-driven decisions. This shift is leading to a workforce that is increasingly analytical and adept at leveraging data to optimize production processes.

Real-time data enables continuous monitoring of production lines, providing insights into machine performance, production rates, and quality control. By utilizing production monitoring software, plant managers can identify bottlenecks, minimize waste, and enhance overall equipment effectiveness (OEE). The ability to make quick, informed decisions based on real-time data is a game-changer, enabling factories to respond swiftly to changes in demand and maintain high levels of productivity.

Seeing these manufacturing insights can only be a game changer if the team is ready to take action. Data only shows the path towards optimization. The company culture needs to be ready to choose the right metrics to take action. The right system will continue to grow with the factory as each new insight is analyzed, explored, and optimized.

“You can look at your speedometer to see your speed, but if you don’t have a speedometer, you have no idea how fast you’re going.”

John Bowers, Oral BioTech
Tacony Maximizes Visibility By Tracking Product from Production Floor to Delivery

Tacony originally came to Mingo Smart Factory seeking help with their outdated manual reporting and a 14-week backlog in their West Chicago furniture plant. The first step to gaining visibility into their factory was to install sensors and a system of automatic data collection through a manufacturing dashboard. Tacony reduced that backlog by 60% within 9 months to gain half a million dollars in revenue. They also took initiative in implementing Mingo into their distribution system. Now they have the full picture of how product moves through the plant to the warehouse, and eventually to the hands of customers.

Increased Collaboration Between Humans and Machines

As automation becomes more prevalent in manufacturing, there is a growing trend towards increased collaboration between humans and machines. This collaborative approach, often referred to as cobotics, involves humans working alongside robots to perform tasks more efficiently and safely. Cobots (collaborative robots) are designed to assist human workers by taking on repetitive or hazardous tasks. This allows humans to focus on more complex and value-added activities.

The integration of cobots into manufacturing processes not only enhances productivity but also improves workplace safety and job satisfaction. Workers are no longer confined to monotonous and physically demanding tasks. Instead they can instead engage in roles that require critical thinking and creativity. This shift is leading to a more dynamic and fulfilled workforce, capable of leveraging the strengths of both humans and machines.

IoT is just an enabling technology that fits within larger systems. Manufacturers need to understand the plant holistically first. Unlike traditional factories, which often operate in silos with limited connectivity and visibility, a smart factory embraces connectivity and digitization across all facets of production. Every machine, workstation, and assembly line is equipped with sensors and connected to a centralized data infrastructure. This enables real-time monitoring and control of production activities.

Key Features of a Smart Factory
  1. Real-Time Monitoring and Control: Continuous monitoring of production parameters, equipment performance, and quality metrics, with automated alerts and notifications to promptly address deviations or anomalies.
  2. Predictive Maintenance: Utilizing predictive analytics and condition monitoring to anticipate equipment failures and schedule maintenance activities proactively, minimizing downtime and maximizing uptime.
  3. Flexible Manufacturing: Agile production capabilities enabled by modular and reconfigurable production lines, allowing rapid adaptation to changing product specifications and market demands.
  4. Collaborative Robotics: Integration of collaborative robots (cobots) into production processes to enhance efficiency, safety, and flexibility, enabling human-robot collaboration in tasks such as assembly, handling, and inspection.

Adoption of Flexible Work Practices

Technological advancements are also driving the adoption of more flexible work practices within the manufacturing sector. Remote monitoring and control systems, enabled by IoT (Internet of Things) and cloud computing, allow plant managers and engineers to oversee operations from anywhere. This flexibility is particularly valuable in today’s context, where remote work has become more common since the COVID-19 pandemic.

Flexible work practices extend beyond remote monitoring to include flexible scheduling and shift patterns. Advanced production monitoring software can optimize shift planning based on real-time data, ensuring that the right number of workers are on the floor at the right times. This not only enhances productivity but also improves work-life balance for employees, making the manufacturing sector more attractive to potential recruits.

Gain visibility on to the plant floor with your machine and operator data in real-time. Mingo Smart Factory provides machine cell OEE, downtime and scrap alerts optimized for with the mobile app. Some features of the mobile app include:

  • Monitor the Plant Remotely
  • Real-Time Metrics
  • Notifications
Mingo Smart Factory Mobile App
Ice Industries Monitors Multiple Locations through the Mingo Dashboard

When the owner of Ice Industries emailed the Director of Operations about the status of a line, Mr. Bishop was able to go into the Mingo Smart Factory dashboard to pull the actual production numbers from the past two months. Some quick analysis revealed that while the OEE showed that the quality and performance was good, the 30-60% availability was dragging down the metrics.

Impact of Real-Time Data and Smart Factory Production Monitoring Software

The impact of real-time data and smart factory production monitoring software cannot be overstated. These technologies are at the heart of the transition from Industry 3.0 to Industry 4.0, and they are paving the way for Industry 5.0. Real-time data provides immediate visibility into production processes, enabling proactive decision-making and rapid response to issues. This level of transparency and control is essential for maintaining high standards of quality and efficiency in modern manufacturing.

Production monitoring software, such as the solutions offered by Mingo Smart Factory, plays a critical role in this transformation. By integrating sensors, IoT devices, and advanced analytics, these systems provide a comprehensive view of the manufacturing process. They collect and analyze data from various sources, presenting it in an accessible format for plant managers and executives.

This capability allows older Industry 3.0 factories to quickly and efficiently upgrade to Industry 4.0 standards. For instance, a factory equipped with legacy machinery can integrate IoT sensors to collect data on machine performance and production metrics. This data is then processed by production monitoring software, providing insights that can be used to optimize operations, reduce downtime, and improve OEE.

Preparing for the Future

Looking ahead, the transition to Industry 5.0 will further emphasize the collaboration between humans and machines, with a focus on personalization and sustainability. Manufacturing plants that have embraced real-time data and smart factory technologies will be well-positioned to make this leap. Industry 5.0 envisions a future where humans and AI-driven machines work in harmony to create customized products while minimizing environmental impact but the data needs to be there first.

To prepare for this future, manufacturing executives and plant managers should continue to invest in advanced technologies, upskill their workforce, and foster a culture of continuous improvement. Embracing these trends will not only enhance competitiveness but also ensure that their factories remain agile and resilient in the face of evolving market demands.

The advancements in technology and AI are driving significant changes in the manufacturing workforce. By understanding and adapting to these trends, manufacturing executives and plant managers can harness the power of real-time data and production monitoring software to transition seamlessly from Industry 3.0 to Industry 4.0 and beyond. This proactive approach will enable them to build a skilled, data-driven, and collaborative workforce ready to meet the challenges and opportunities of the future.

Picture of Alyxandra Sherwood
Alyxandra Sherwood
Digital Marketing Manager @ Mingo Smart Factory I Adjunct Professor @ SUNY Geneseo I Boston Marathoner I Second Street Award Winner I Media Professional with 15 Years Experience