AI in manufacturing: Balancing automation with workforce development for industry 4.0
By Phani Tangirala, COO, Expleo, India
Business leaders of manufacturing firms have prioritised globalisation over decades. This increased emphasis on global relations has resulted in several benefits, including increased market access, unrestricted labour mobility, and a broader range of commodities available to customers. On the other hand, globalisation brings several possible challenges, and firms must address them to manage their workforces efficiently, maintain employee morale, and avoid significantly higher employee turnover. The pressure to boost bottom-line profitability in the face of such problems is apparent. Here, artificial intelligence (AI) in the manufacturing industry comes into play. Combined with its workplace technologies, AI has emerged as one of the most effective methods to empower management and the workforce to accomplish tasks more efficiently with their existing resources.
Importance of AI in the manufacturing industry
AI technologies, machine learning, and robots possess the potential to improve industrial processes by boosting efficiency, enhancing quality control, and lowering costs. AI systems can optimise manufacturing processes, forecast maintenance requirements, and reduce downtime by analysing data in real-time and making swift choices. This may considerably increase overall production and ensure that products are delivered on time. Additionally, AI-enabled robots may automate monotonous and hazardous activities, making the workplace safer and saving people’s time to focus on challenging and creative tasks.
Integration of AI with workforce development
Adoption is crucial for successful AI implementations since it involves more than technical aspects. However, it might be challenging in terms of skill acquisition and workforce acceptability. Manufacturing executives might feel concerned about workforce opposition to AI adoption. Effective change management and training are, therefore, crucial for driving change. Implementing a gradual approach ensures that AI investments are manageable and yield obvious ROI (returns on investment) over time. Integrating AI into the workforce requires a balanced approach that includes external expertise, internal training, and workforce development to manage the intricacies and possible disruptions of the technology, eventually leading organisations to the forefront of the Industry 4.0 era.
Key drivers of industry 4.0
In a study conducted by PwC, it has been determined that India’s manufacturing industry has observed a 20% growth in the adoption of machine learning and artificial intelligence in the last two years. The main reason behind this growth is the benefits the former sector obtained while driving the revolution of Industry 4.0. At its core, Industry 4.0 is the integration of digital technology, data analytics, and automation to build a pertinent manufacturing environment. Following are some of the critical components of Industry 4.0:
IOT devices: These devices promote the collection and exchange of data between machines, products, and systems while building a network of information and delivering real-time insights into multiple manufacturing process components.
Analytics and big data: Big Data analytics enables manufacturers to identify relevant patterns, trends, and associations, consequently boosting data-driven decision-making and predictive maintenance.
Automation: Robots and automation not only accelerate manufacturing but also improve precision and flexibility. For instance, collaborative robots operate alongside human operators in order to achieve a more harmonic and effective execution.
Artificial intelligence: AI plays an important role in Industry 4.0 by allowing machines to gain insight and adapt to evolving environments. In addition, machine learning algorithms analyse data, find trends, and optimise processes, resulting in increased efficiency, less downtime, and better overall performance.
Perks of integrating AI for workforce management
The amalgamation of the rapid decision-making capacity of AI-driven systems with Industry 4.0 technologies has significantly revolutionised and benefited operations and workforce management. Here’s a look at some of the potential benefits of artificial intelligence in the manufacturing industry:
Human error leads to some of the most severe risks to operational efficiency in labour-intensive industries, such as manufacturing. One of the most effective methods to reduce such risks is to involve automated inventory management platforms that leverage IoT sensors to track products precisely and update records and ordering systems as required.
Certain types of automation can reduce the unnecessary exposure to hazards employees confront in their line of work. For example, cobots collaborate with human workers to tackle the most risky or complicated elements of their tasks.
In many circumstances, AI and Industry 4.0 technology are not intended to replace the most complex or creative aspects of human jobs. Rather, these systems excel at automating repetitive and time-consuming operations. As a result, human employees are no longer required to perform duties that they may find challenging or stressful, enabling them to focus on the elements of their jobs that they like the most.
Bottom line
The task of maintaining the balance between human beings and automation requirements in the industrial and manufacturing sectors is a challenging but vital endeavour that necessitates strategic planning, collaborative effort, and creative thinking. Also, it has become imperative for manufacturers to remember that automation is not a substitute for human labour; rather, it augments employee potential with the accuracy and consistency of machines. By using this forward-thinking strategy, companies can manage the intricacies of the contemporary industrial world and position themselves for future success.
