The explosive growth of automation has revolutionized the manufacturing industry. Now integrated into all aspects of supply chain networks, automation is necessary for any efficient supply chain. Increasing the pace of manufacturing is crucial to keep up with the ever-growing demand faced in the consumer culture we live in. In the past, automation primarily took over the manual aspect of repetitive and laborious tasks. Thanks to recent developments, automation can optimize nearly every supply chain process, including inventory, planning, distribution, shipping, and more. Not only does automation make on-demand processing more accessible, but it has also made it more efficient and lower cost. You’ve heard of automation, but how does intelligent automation differ? Intelligent automation is the overarching umbrella under which artificial intelligence (AI) and robotic process automation (RPA) reside. This includes machine learning, learning technologies, workflows, and everything in between. AI enables insight-driven analytics, decision-making, and personnel management, while RPA automates processes and reduces human participation in them. Essentially, it combines bots and software intelligence in the production process. These solutions can be used in various ways but are extremely useful when applied to solving operational business problems, such as workflows and predictive analytics and maintenance. All of these features and benefits make intelligent automation an obvious solution for the supply chain manufacturing process.
Manufacturers already utilize workflow designs in their business operations, and many of those are partially automated. But, by maximizing the automation of these workflows, manufacturers can save even more time and thus money. By leveraging robotic process automation workflow optimization and AI’s ability to process more significant volumes of data at higher speed, manufacturers can receive a greater scope of data to be analyzed. While more data to analyze may seem like more work, intelligent automation takes care of that for you. In reality, intelligent automation will process this data and translate it into greater insights and evaluations, allowing you more accurate information for decision-making.
Incorporated with deep learning, workflow automation has become a growing aspect of intelligent automation. An excellent feature is its natural language processing. This capability makes it possible to turn free-form text into business logic, such as processing sales order instructions that must be routed to specific departments. Previously this task would have required manual interpretation from a team member, but with AI-enhanced automation, it will be taken care of with incredible speed. Now, team members can entrust intelligent automation with tedious and repetitive tasks and focus on higher-value projects.
Predictive Analytics and Maintenance
Likely, manufacturers are already recording this data, so why not simplify that process? Using the data they are already recording, manufacturers can use predictive analytics to solve new and future problems and then facilitate product engineering. Using historical data, intelligent automation can analyze past and present market trends, compare them to current operational data, and predict future demand. Manufacturers can then use this information to may decisions on production, inventory, and distribution to meet demand and maximize their operations. Not only is does this make for more informed decisions, but it's also a significant time-saver for manufacturers as it replaces the need for manual calculations. Furthermore, it eliminates the risk of human error, provides more accurate results, and notices anomalies before products enter quality assurance.
The predictive maintenance capabilities of intelligent automation even extend beyond demand predictions. These solutions also allow machines to report back when maintenance is needed, reduce unplanned downtime, and prevent timely and expensive breakdowns. Speaking of unexpected disruptions, predictive maintenance is also a beneficial tool for distribution, transportation, and shipping. Intelligent automation systems can also disruptions such as weather and traffic delays, notifying manufacturers of late shipments. This allows manufacturers to reroute shipments or notify expecting parties of a delay.
Intelligent Automation in Manufacturing
IA has accelerated the new industrial revolution, known as Industry 4.0. Especially in the supply chain and manufacturing industry, companies now heavily rely on IA and AI to process and interpret data. While instrumental by themselves, these solutions are incredible when combined with other technologies such as IoT, ML, robotics, and countless more. In the past, there were concerns that robots and automated technologies would replace human labor, but that has not been the case. Instead, intelligent automation supplements humans, alleviating them of tedious and repetitive tasks and providing them with the tools to make better decisions.
This is evident specifically in the manufacturing industry. One example of this is through an automated factory floor. Physical robots and automated equipment can perform almost any manufacturing process in a factory today, leaving humans to complete strategic tasks rather than manual. As mentioned before, it is also excellent in optimizing workflows and predictive analytics. With IA, manufacturers can process enormous amounts of data at an expedited speed to streamline ordering, procurement, appointment scheduling, and alerting. They will also have the capacity to fix aberrations proactively rather than reactively. This is significant in preventing outages, breakdowns, and downtime. With intelligent automation, maintenance engineers can anticipate errors and address them before equipment and operations are significantly impacted. Another great ability is machine vision. Automated technology enables more thorough quality inspection and is more detailed and reliable than when conducted by humans.
Pros and Cons
Intelligent automation is an incredible resource for manufacturers, but like anything, it has drawbacks. While you likely already have many of the technologies needed for IA implementation, you will still need to develop an implementation strategy and choose the right tools. As with the implementation of any new solution, it's essential to understand its capabilities to maximize its value and data. As a result, you may also have to restructure some existing systems and retrain team members to become familiar with the new system. With this, you will need to teach necessary metrics and assign tasks accordingly. Overall, creating a proper IT environment and technological ecosystem is a hefty task, but when done thoroughly, your systems will work together seamlessly, providing you a significant competitive advantage.
While it is important to recognize the disadvantages of intelligent automation, they are heavily outweighed by its countless benefits. First and foremost, you will more efficiently use equipment and manpower, focusing your team members on critical issues rather than mundane work. As a result of this, you will see increased effectiveness across the entire company, thus experiencing lower costs and higher ROI – direct results of enhanced decision making. You will also see enhanced cybersecurity, as you can regulate user access to your systems. Finally, you will provide a seamless customer experience to your end-users, providing them with efficient, timely, and quality products. Intelligent automation is a resource that cannot be overlooked. IA will optimize your supply chain and transform the manufacturing industry as we know it.
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