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In 2006, experts at a National Science Foundation workshop proposed the idea of “smart manufacturing.” Back then, it might have seemed like something out of science fiction. Today, however, smart manufacturing is a real and important industry trend. 86% of manufacturing executives believe smart factory solutions will be the primary drivers of competitiveness over the next five years as these solutions offer significant benefits in quality, efficiency, and sustainability.
Legislations like the Infrastructure Investment and Jobs Act (IIJA) and the Inflation Reduction Act (IRA) support sustainable manufacturing practices in the U.S. Even so, manufacturers are dealing with challenges like talent crunch, economic uncertainties and supply chain issues.
Smart manufacturing has emerged as a key solution to these challenges.
What is Smart Manufacturing?
Smart manufacturing, or smart factories, is not just one technology. Instead, it’s a way of using different technologies like AI, and RPA (Robotic Process Automation) to improve business processes and create smarter assembly lines. By adopting smart manufacturing practices, companies can increase efficiency and agility in daily operations and achieve Industry 4.0 goals.
Smart Manufacturing and ROI Benefits
Beyond modernization, smart factories offer a multitude of operational and financial benefits that significantly impact a company’s bottom line.
According to a recent McKinsey report, Industry 4.0 initiatives like smart manufacturing can provide significant value across various dimensions.
- 30 to 50 percent reduction in machine downtime
- 10 to 30 percent increase in throughput
- 15 to 30 percent improvement in labor productivity and
- 85 percent more accurate forecasting
Increased Efficiency and Productivity: Real-time data analysis helps identify bottlenecks, optimize processes, and ensure machines run optimally, leading to more output with fewer resources.
Reduced Downtime and Improved Maintenance: Predictive maintenance using sensor data minimizes unplanned downtime by identifying potential equipment failures before they happen, keeping production lines running smoothly.
Enhanced Quality Control: Automated quality checks integrated throughout the process reduce defects, allowing for early detection and correction, minimizing wasted materials and rework.
Improved Supply Chain Management: Better inventory management with real-time data minimizes carrying costs associated with holding excess stock.
Greater Flexibility and Scalability: Data allows for faster adjustments to production schedules and resource allocation, enabling companies to adapt to changing demands and be more responsive.
Smart Manufacturing Technologies
1. Cloud Computing and Big Data Analytics
Traditionally, manufacturing units relied on experience and intuition. But smart factories leverage cloud computing and big data analysis to help companies make data-driven decisions. Every day, factories generate a vast amount of information, from machine sensors to supply chain data. Cloud provides the infrastructure for storing, processing, and accessing all this data.
Big data analytics solutions like Microsoft Fabric can be used to make sense of the raw data whether structured, unstructured or semi-structured. Microsoft Fabric can help you analyze this data, identifying patterns and anomalies to optimize production schedules, minimize downtime, and ensure consistent product quality.
2. Robotic Process Automation
Robotic Process Automation (RPA) is a technology that can mimic human actions like data entry and mouse clicks, saving time and resources. One prominent use case of RPA in manufacturing is in inventory management. RPA bots can monitor inventory levels in real-time across multiple systems, generate reorder notifications, and even place orders with suppliers automatically, minimizing the risk of stockouts or overstocking. RPA offers manufacturing companies the opportunity to increase productivity, reduce costs, and improve overall operational efficiency through automation of routine tasks.
3. Artificial Intelligence (AI)
AI is used in various manufacturing applications, including quality control, and process optimization. AI algorithms can analyze data to identify patterns and trends, helping manufacturers make better decisions and improve efficiency. Recent statistics show that manufacturers lose a staggering 800 hours of production time every year due to unexpected equipment failures. Manufacturers can gain valuable insights into machine health, by collecting real-time data from sensors and devices and using AI to proactively predict maintenance needs.
4. Augmented Reality (AR) and Virtual Reality (VR)
AR and VR are being used for training, maintenance, and remote collaboration in manufacturing. AR overlays digital information onto the real world, allowing workers to see instructions or data while performing tasks. VR creates immersive simulations for training or troubleshooting complex equipment. By implementing AR and VR, manufacturers can allow workers to practice risky procedures in a safe environment or facilitate remote guidance.
5. Digital Workplace
The manufacturing sector faces a looming retirement wave, often referred to as the silver tsunami. A 2021 report by Deloitte and the Manufacturing Institute predicts a significant workforce gap, with 3.8 million jobs needing to be filled by 2033. A top concern for many manufacturers is attracting and retaining fresh talent who look for flexibility, connectivity, and meaning. To address this challenge, manufacturers can turn to digital workplace solutions as a part of Industry 4.0 initiatives.
A digital workplace platform that is built on MS SharePoint can serve as a central repository to capture the wealth of knowledge from experienced staff before they retire. This can include things like standard operating procedures (SOPs), troubleshooting guides, and even recorded video tutorials. It can connect people, improve collaboration, and ensure everyone is on the same page.
Smart Manufacturing Challenges
- IT/OT Convergence: Traditionally, manufacturing units treat Operational Technology (OT) like machines, sensors and Information Technology (IT) like data storage, networks as separate entities. This siloed approach can be a major challenge when transitioning towards a smart factory. Disconnected OT and IT systems create data silos, making it difficult to optimize processes, identify bottlenecks, and make data-driven decisions.
- Cultural Shift and Workforce Training: Transitioning to a smart factory necessitates a cultural shift within the organization. Training and reskilling the workforce is crucial to ensure employees are prepared for the change.
- Legacy Systems and Infrastructure: Many existing manufacturing facilities rely on legacy equipment and outdated IT infrastructure. Upgrading these systems can be expensive and time-consuming, creating a hurdle to implementing smart manufacturing technologies. Low-code application development solutions can help manufacturers to overcome the hurdle of legacy systems when implementing smart factories.
- Cost and Return on Investment (ROI): Implementing smart manufacturing involves significant investment in technologies, infrastructure changes, and workforce training. Instead of a massive overhaul, manufacturers can adopt a phased approach, focusing on areas with the clearest ROI first.
Make the Transition to Smart Manufacturing with Eleviant CTG
Transitioning to a smart factory is a big step, and it requires careful planning and strategy. At Eleviant CTG, we understand the challenges of making this transition seamlessly while keeping up with production. We also recognize the critical role of bridging the gap between IT and OT systems (IT/OT convergence) to unlock the full potential of smart manufacturing. We can guide you through exploring how smart factory technology can be your solution. Partner with Eleviant CTG to embark on your journey to smart manufacturing.
