How Artificial Intelligence is Transforming the Manufacturing Workforce

AI is evolving rapidly and the companies that choose to leverage this technology will quickly transform with it.

Mnet 193259 Artificial Intelligence
Nick CastellinaNick Castellina

While Artificial Intelligence (AI) is one of the most disruptive technologies impacting manufacturing, it is also one of the most controversial. The race to implement AI is accelerating faster than ever before, and we are already witnessing major progress in the Robotics, Machine Learning and Predictive Analytics as a result. From speeding shop floor operations and automating routine decisions, to advising on executive-level decisions — AI is already creating value in manufacturing by automating and streamlining the entire ecosystem. In fact, it has become so instrumental that some wonder if factories will rely on machines altogether, eliminating jobs.

While this can be a sensitive subject, managers should weight the benefits and risk of AI and learn they can best deploy it in their enterprise. To stay competitive, manufacturers must understand the latest trends, keep pace with change, and not let fear of the unknown impede progress. AI is evolving rapidly and the companies that choose to leverage this technology will quickly transform with it. 

The State of AI Today

AI technology is advancing at such a rapid rate that it is difficult to stay up-to-speed on best practices. It is being embedded within a wide range of technologies, from ERP solutions with built-in Business Intelligence capabilities, to Networked Supply Chains using Predictive Analytics. AI is also nudging users along guided paths and supplementing decision points with tips and results from previous similar incidents. In such cases, the user may not even realize that AI is providing the insights and simply see the guidance as what is expected of modern computing.     

More specifically, here is how AI is applied in modern manufacturing:

Automation. In industrial manufacturing, several routine and administrative tasks can be automated by AI. Users can create workflows, which allow data points to create reports, place re-orders, signal notices, trigger reactions, flag potential hazards, dispatch crews, reserve parts or reroute materials. These cases of automation range from modest time-savers to huge improvements in uses of time and resources.

AI and IoT. AI and the Internet of Things (IoT) work together to interpret and determine the seriousness of flagged data points received from sensors. Sensors generate such vast amounts of data, it would be useless without the ability to sort and identify the significant points. Using AI, the system can spot anomalies, such as early warning signs that an asset may require maintenance.

Personal Assistants. An excellent example of how AI is improving manufacturing is the Personal Assistant. This technology uses Natural Language Processing to answer questions, perform functions, interact with the user and provide sound recommendations. Not only are Personal Assistants convenient, they can be valuable safety aids for hands-free questions and data queries, such as when the user is driving a forklift or servicing machinery on an elevated platform.

Facial Recognition. This technology offers the capability of identifying and verifying individuals based on images, which can greatly benefit the manufacturing industry by issuing security clearances. Even more impressive, AI applications for recognizing images can provide visual confirmation of quality control. The same type of technology that recognizes faces can determine if red jelly beans are being routed to the correct packaging.

Detecting Fraud. Manufacturers can leverage AI to monitor for anomalies, flag atypical customer orders and monitor for compliance with regulations and safety mandates. Today, modern software can act as an always-present watchdog to spot unusual activities that require human investigation. Simple messages such as “are you sure you want to do that” are often the trigger employees need to further consider or investigate discrepancies. 

Predictive Analytics. BI solutions with AI built-in are extremely valuable in purchasing and managing the supply chain, allowing managers to project demand and estimate resources needed with high levels of accuracy. Users can evaluate clearly defined sets of recommendations and make well-informed decisions based on scientific reasoning. AI technology recognizes patterns, expands the knowledge base, and discovers cause-and-effect relationships.

Machine Learning. From buying trends, to pricing projections — machine learning can be applied to predict outcomes and forecast the future. It can also streamline complex decision-trees, apply data-based science, and proceed with defined actions, based on parameters learned from user input. More specifically, companies that are highly risk adverse can ensure their automated systems follow protocols that align with “play it safe” policies, such as maintaining safety stock or weighing vendor selections to favor reliability over cost.     

AI plays a critical role in helping humans do their jobs. It is a tool, not a replacement, for enhancing decision-making and business insight.

What Holds Businesses Back from Leveraging AI?

For many workers, AI presents a dystopian future where the human work is obsolete. While it is easy to envision a future where machines run themselves and robots methodically weld and bolt components in place without a human in sight, humans will still play an essential role in operations. The number of smart factories that incorporate technology is increasing, Which means having a skilled workforce is more important than ever.

Most manufacturing teams will quickly realize that the benefits of AI far outweigh any false concerns about eliminating jobs or sci-fi visions of an apocalyptic world of renegade robots.

The Future of Manufacturing

There is an extremely high demand for technicians who are skilled in AI, though they are difficult to recruit While some manufacturers are reskilling their workforce, others are turning to third party resources and software providers to acquire expertise. When a manufacturer deploys technology in the cloud, the host’s experts become the manufacturer’s experts, continually updating the technology as innovations are developed, while offering back-up and security.

Working with a technology provider also ensures the most current and effective uses of AI are adopted. Updating processes and leveraging new technologies, like AI, are critical to remaining relevant and competitive. This also means modernizing how decisions are made and the way business intelligence tools are leveraged for predictive insights.

Nicholas Castellina is Director of Industry and Solution Strategy at Infor.

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