By utilizing real-time data and advanced analytics, manufacturers can optimize their processes and reduce costs, resulting in higher efficiency and increased profitability.
Smart manufacturing is a cutting-edge approach to industrial production that integrates advanced technologies, such as artificial intelligence (AI), the Internet of Things (IoT), and big data analytics. By leveraging these technologies, smart manufacturing enables manufacturers to make data-driven decisions helping them optimize their operations, reduce costs, and enhance product quality.
Smart manufacturing has become increasingly important due to several factors.
First, customer expectations for customized products and rapid delivery times have grown. This leads manufacturers to seek innovative ways to increase their efficiency and agility. Second, the need to reduce production costs and waste while maintaining product quality has become a top priority for manufacturers. Finally, the emergence of Industry 4.0 and the digitization of the manufacturing process have created a demand for smarter and more connected production systems.
This article aims to explore the use cases for smart manufacturing and their impact on production. By examining how smart manufacturing enables predictive maintenance, quality control, and supply chain optimization, we will illustrate the practical benefits of this innovative approach to manufacturing. Through real-world examples, we will showcase how smart manufacturing has helped manufacturers increase productivity, reduce downtime, enhance product quality, and lower costs.
Predictive maintenance is a common practice in smart manufacturing. This proactive approach to equipment maintenance uses advanced technologies and data analysis to predict when equipment failures are likely to occur.
By monitoring equipment performance in real time and analyzing historical data, predictive maintenance allows manufacturers to identify potential issues before they become serious problems. This enables the business to address them proactively and avoid costly downtime.
Additionally, machine learning algorithms can use this data to identify patterns and predict equipment failures, enabling manufacturers to schedule maintenance at the optimal time to avoid disruptions to production.
Some of the benefits of predictive maintenance in smart manufacturing are:
Downtime Reduction: Through prediction and prevention of equipment failures before they occur, predictive maintenance reduces downtime, increases equipment reliability, and enhances overall productivity.
Maintenance Cost Savings: Manufacturers can schedule maintenance activities at desirable times, avoiding unnecessary downtime and the associated costs of emergency repairs.
Product Quality: Because the equipment is operating at peak performance, the likelihood of defects caused by faulty equipment is reduced.
TVH is one of the world’s largest providers of industrial vehicles, such as forklifts. In 2017 they started a journey into predictive maintenance using IoT-enabled forklift devices. This allowed the company to remotely diagnose and categorize repair events, which helped them optimize their technician scheduling and parts management.
As a result of the predictive maintenance program, TVH saw maintenance cost reductions of 30% and noted a “significant increase in the uptime of the machines.”
Predictive maintenance is a critical component of smart manufacturing and is transforming the way manufacturers approach equipment maintenance, leading to significant improvements in efficiency, productivity, and profitability.
Smart Manufacturing Use Case 2: Quality Control
Quality control plays an essential role in ensuring that products meet customer expectations and regulatory requirements. The aim is to minimize the risk of product recalls and negative impacts on brand reputation.
Smart manufacturing technology has revolutionized quality control by enabling real-time monitoring and analysis of production processes. With smart manufacturing systems, manufacturers can collect and analyze data from sensors and other connected devices throughout the production process. This data can then be used to identify and diagnose issues, adjust production processes in real time, and reduce the risk of defects and non-conformities.
In addition, smart manufacturing can also leverage artificial intelligence and machine learning algorithms to detect patterns and anomalies in data, enabling predictive maintenance and proactive quality control measures.
Some of the benefits of smart manufacturing for quality control are:
Improved Quality: By implementing smart quality control measures, manufacturers can minimize the risk of defects, improving product quality and customer satisfaction.
Risk Reduction: Smart quality control also reduces the risk of product recalls, which can be costly both in terms of financial losses and damage to brand reputation.
Efficiency: Manufacturers can optimize processes by collecting and analyzing data in real time, improving efficiency and reducing waste.
As smart manufacturing technology continues to advance, it is clear that quality control will play a critical role in ensuring the success and competitiveness of modern manufacturing operations.
A large adhesive manufacturer wanted to get a good handle on its quality control process. They thought there were improvement possibilities.
They conducted an assessment that revealed an insufficient awareness regarding the sensitivity of the quality assurance parameters and their impact on output quality. They also found opportunities for real-time monitoring and process control improvements. The existing deficiencies led to variations in yields, resulting in increased inventory, missed customer deadlines, and significant revenue losses.
They implemented a quality platform that was able to analyze the historical data. The model gave them a good understanding of the specific variables most affecting quality. Thus they could dial-in on the most critical variables of their processes.
The model was eventually scaled to 33 plants with a potential savings of over $300 million.
Smart Manufacturing Use Case 3: Supply Chain Optimization
With smart manufacturing, companies can track and analyze real-time data from across the supply chain. This helps them make more informed decisions about production, inventory management, and distribution.
Companies can streamline production processes to save money on materials, labor, and other overhead expenses. Smart manufacturing also helps companies optimize their inventory levels, which reduces the risk of overstocking or stockouts. This means that companies can better manage their working capital and allocate resources more effectively.
Another benefit is improved agility. With real-time data insights, businesses can quickly adapt to changes in demand, supply, or other market conditions. Smart manufacturing enables companies to make production adjustments on the fly, which means they can respond more quickly to customer demands, reduce lead times, and improve delivery times.
A company wanted to increase its market share and thought its supply chain was holding them back. They employed an IoT platform with analytics to examine their supply chain network.
They created an asset-tracking solution that used sensors installed in end-of-line products. This solution helped workers locate inventory more efficiently and match it with scheduled deliveries, resulting in a more streamlined operational process.
Next, the sensor data was then fed into apps and dashboards, providing real-time insights into the manufacturing process and shipyard operations. With this information, the business was able to easily monitor the status of work-in-progress inventory and factories.
The company reduced unplanned movements, leading to a 3-4 percent increase in labor efficiency and a reduction in excess finished goods inventory. Additionally, better signaling to the shipping function resulted in a two-day product pick-up time reduction. Improved forecasting also enabled on-time delivery to dealers, ultimately strengthening business relationships and customer loyalty.
Smart manufacturing technologies such as predictive maintenance, quality control, and supply chain management are all effective production improvement strategies. By utilizing real-time data and advanced analytics, manufacturers can optimize their processes and reduce costs, resulting in higher efficiency and increased profitability.
These use cases also enable proactive decision-making and prevent potential issues, leading to improved customer satisfaction and loyalty. As the manufacturing industry continues to evolve, the adoption of smart manufacturing technologies is becoming increasingly important for businesses to remain competitive and stay ahead of the curve.