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Top Automation Trends for Manufacturing: 2024
  • Manufacturing
  • Apr 26 2024

In the wake of a challenging year marked by downturns in manufacturing output, new orders, and employment levels throughout much of 2023, the manufacturing industry stands now ready for renewed transformation. Faced with the need to rebound from setbacks and navigate a swiftly evolving landscape, manufacturers are intensifying their searches for innovative solutions to enhance efficiency, reduce costs, and secure their competitiveness. 

Today, automation plays a crucial part in many manufacturing operations – and signs are that in 2024, it’s set to become more important than ever. With automation becoming more accessible and delivering clear economic and efficiency benefits, it’s not surprising that global figures show demand for robotics continues to surge. Projections indicate that 600,000 units will be installed around the world in 2024 alone, highlighting the pivotal role automation is set to play in reshaping manufacturing processes and outcomes. 

As the manufacturing sector continues to embrace the transformative potential of automation, backed by supportive legislation globally, it is also looking to harness emerging trends and technologies to streamline operations, optimise resource utilisation, and unlock new paths for growth. 

In this article, we’ve explored five of the top trends set to redefine automation in manufacturing in 2024, offering insights into the innovations shaping the future of the industry. 

1. AI-driven Automation 

As machinery and equipment companies bolster their technological capabilities, there’s a substantial focus on investing in artificial intelligence (AI). The AI market in industrial machinery, encompassing intelligent hardware, software, and services, is projected to soar to $5.46 billion by 2028, according to the Business Research Company

AI offers solutions to the primary challenges encountered by machinery and equipment executives, ranging from supply chain volatility and cost pressures to the shortage of skilled workers. In this scenario, AI emerges as an effective solution, offering a way to tackle these pressing issues head-on. 

For many machinery executives, AI adoption isn't just an option; it's a necessity. Across the advanced manufacturing sector, a staggering 75% of executives pinpoint adopting emerging technologies like AI as their top priority for engineering and R&D. However, despite most companies having gathered the necessary data needed for AI implementation, most companies are not yet using it. 

So, what sets the pace for success in AI adoption? It begins with advanced machinery companies identifying their core business challenges and envisioning how AI can enhance processes and overall performance. This means assessing different AI modalities, such as machine learning (ML) or generative AI, to understand their value proposition. Early adopters are already reaping the benefits, leveraging AI to address critical issues across procurement, assembly, maintenance, quality control, and warehouse logistics. 

Take predictive maintenance, for example. By harnessing AI algorithms, companies can predict equipment failures before they occur, minimising downtime and optimising maintenance schedules. Similarly, AI-powered quality control systems can swiftly identify defects and anomalies in production lines, ensuring product integrity and minimising waste. 

Looking ahead, the demand for AI expertise in manufacturing is poised to soar. Companies are likely to be hiring for roles such as:
 

  • AI Engineers – these professionals design and develop artificial intelligence (AI) systems and algorithms tailored to optimise manufacturing processes, enhancing efficiency and productivity. 
     

  • Data Scientists – they analyse vast datasets to extract valuable insights and patterns, empowering manufacturing decision-makers with actionable intelligence for informed decision-making and process optimisation. 
     

  • Machine Learning Specialists – these specialists leverage machine learning algorithms to train AI models that improve automation systems' performance, enabling predictive maintenance, quality control, and demand forecasting in manufacturing environments. 
     

  • Automation Technicians – skilled in the installation, maintenance, and troubleshooting of automated systems, automation technicians ensure the seamless operation of AI-driven machinery and robotics on the factory floor, minimising downtime and maximising productivity. 
     

  • AI Integration Specialists - with expertise in integrating AI technologies into existing manufacturing systems and workflows, these specialists facilitate the seamless adoption of AI-driven automation, unlocking new levels of efficiency and innovation in production processes. 


As manufacturing continues its path towards AI-driven transformation, companies that adeptly integrate AI solutions into their processes and backend systems are poised to surge ahead in the competitive landscape. 

 

2. Collaborative Robotics (Cobots) 

The use of collaborative robots - or "cobots" - in the manufacturing sector has expanded significantly. These robots are designed to work alongside humans in shared spaces, improving efficiency, reducing errors, and augmenting workforce productivity. Equipped with advanced sensors and safety features, cobots facilitate safe collaboration with human workers. 

One of the main reasons behind the rising adoption of collaborative robots is their ability to enhance efficiency and flexibility on the factory floor. Unlike traditional industrial robots that are often confined to safety cages, cobots can operate in close proximity to humans without posing a safety risk. This allows for seamless collaboration between human workers and robots, leading to optimised workflows and increased productivity. 

There have been several case studies that highlight the successful implementation of cobots across a number of industries, showcasing their versatility and effectiveness in different manufacturing environments. For example, in assembly tasks, cobots have demonstrated the ability to perform repetitive and monotonous tasks with precision, resulting in a significant reduction in production costs. Cobots also excel in machine tending roles, where they can operate machines, load parts, and unload finished products, leading to a notable increase in overall production output.  

While the adoption of collaborative robots brings about various benefits, such as increased efficiency, productivity, and safety, it also presents certain challenges. One such challenge is the initial investment required for implementing cobots, which may be simply too high for some small to medium-sized enterprises (SMEs). Integrating cobots into existing manufacturing processes may require training and upskilling for existing workforce members, which in turn, takes further time and financial investment. 

Due to the growing adoption of collaborative robotics in manufacturing, across 2024 companies are likely to be hiring for roles such as:
 

  • Cobotic System Integrators – professionals responsible for designing, programming, and integrating cobots into manufacturing processes. 
     

  • Robotics Technicians – skilled technicians tasked with maintaining and troubleshooting cobotic systems to ensure smooth operations. 
     

  • Automation Engineers – engineers specialised in developing automation solutions and optimising manufacturing workflows using collaborative robotics. 
     

  • Manufacturing Technologists – technologists involved in the strategic planning and implementation of cobotic systems to enhance manufacturing efficiency. 
     

  • Quality Assurance Specialists – professionals responsible for ensuring the quality and reliability of products manufactured with the assistance of cobots. 


As the demand for collaborative robotics continues to grow, these roles will play a crucial part in driving innovation and efficiency in the manufacturing industry. 

3. Edge Computing for Real-time Insights 

Edge computing represents a pivotal advancement in industrial automation, offering real-time data processing and analytics capabilities that are revolutionising decision-making and process optimisation in manufacturing settings. Unlike traditional centralised computing models, edge computing brings data collection, processing, storage, and analysis closer to the point of data generation, enabling manufacturers to extract actionable insights and drive operational efficiencies in dynamic production environments. 

The evolution of manufacturing since the industrial revolution has led companies to aim at building 'smart factories' that can work mostly on their own and be as efficient as possible. With the Internet of Things (IoT) at the forefront, connectivity has become the foundation for unlocking valuable data from industrial machines, paving the way for transformative growth and improvements in productivity and performance.  

In a smart factory's edge computing architecture, cloud services are indispensable for handling their huge amounts of data. However, edge computing devices offer a local alternative, processing and analysing data at its source, thereby ensuring real-time availability and actionable insights for immediate operational enhancements. By moving computational power closer to where it's needed, on the factory floor, edge devices help reduce delays, improve security, and cut costs compared to relying solely on distant cloud-based systems. 

There are a range of benefits to edge computing in manufacturing. Firstly, it facilitates in-depth insights into machine performance, enabling rapid responses to anomalies and proactive planning for predictive maintenance – this in turn means companies can minimise production downtimes. By processing data locally, edge computing also reduces the need for transmitting all data to the cloud, mitigating storage costs and bandwidth requirements while ensuring data availability in real-time for on-premises sharing with stakeholders, making operations that bit faster and cheaper. 

Edge computing allows manufacturers to offer new services, such as remote software updates, enhancing customer satisfaction, and supports the drive for further innovation. The convergence of multiple functions on edge devices enables seamless remote management of software and devices, streamlining operations and enhancing scalability. 

Here are some of the top roles companies will likely be hiring in to support an increase in edge computing:
 

  • Edge Computing Engineers – design and develop edge computing solutions, including hardware and software components, to optimise data processing and analytics at the network edge in manufacturing environments. 
     

  • IoT Solutions Architects – architect end-to-end IoT solutions, integrating edge devices, sensors, and cloud platforms to enable seamless data flow and actionable insights for manufacturing operations. 
     

  • Data Analysts specialising in Edge Analytics – analyse data generated by edge devices in real-time to derive valuable insights, identify patterns, and drive informed decision-making for process optimisation and predictive maintenance in manufacturing. 
     

  • Cybersecurity Specialists for Edge Devices – implement and maintain robust security measures to protect edge computing infrastructure and devices from cyber threats, ensuring the integrity, confidentiality, and availability of manufacturing data and operations. 
     

  • Edge Computing Project Managers – oversee the planning, execution, and implementation of edge computing projects in manufacturing, coordinating cross-functional teams, managing timelines, and ensuring successful deployment and integration of edge solutions to meet business objectives. 


Edge computing forms the basis for intelligent, digital connections in manufacturing, allowing for gathering, storing, and analysing machine data right where it's generated. This setup also supports the introduction of innovative services and enhances operational performance in the Industry 4.0 era.  

 

4. Digital Twins for Simulation and Optimisation 

The concept of digital twins has emerged as a game-changing solution within automated manufacturing, offering unparalleled capabilities in simulating and optimising production processes. Factory digital twins provide a comprehensive model of the factory floor, leveraging real-time data to simulate outcomes and enable "what-if" analyses across various production scenarios. 

Digital twins play a key role in validating designs, optimising layouts, and estimating inventory sizes during the initial investment and build of greenfield factories. These digital replicas not only validate layout designs but also evaluate spatial parameters for assets, such as clearances and ergonomics, ensuring optimal operational efficiency from the outset. In established operations, digital twins prove invaluable in predicting production bottlenecks and optimising production schedules. By modelling complex processes with high fidelity using live data, they uncover hidden inefficiencies and enable informed decision-making, ranging from line balancing to real-time production optimisation. 




Looking ahead, the future potential of digital twins in manufacturing is promising. As automation and AI continue to advance, digital twins are poised to evolve into indispensable tools for manufacturers worldwide. To leverage this transformative technology, companies are likely to hire individuals with expertise in various roles, including:
 

  • Data Engineers or Scientists – to manage and analyse vast amounts of manufacturing data. 
     

  • Industrial or Manufacturing Engineers – to design and implement digital twin solutions tailored to specific operational contexts. 
     

  • IT Architects – to integrate disparate data sources and develop scalable digital twin architectures. 
     

  • Operations Managers – to translate insights from digital twins into actionable strategies for process optimisation. 
     

  • AI and ML Specialists – to enhance digital twin capabilities through advanced algorithms and predictive analytics. 


Digital twins signify a transformative change in manufacturing, enabling companies to streamline processes, manage risks effectively, and foster innovation within an increasingly competitive market. As the technology continues to evolve, embracing digital twins will be essential for manufacturers striving to stay ahead of the curve and unlock new opportunities for growth and efficiency. 

 

5. Sustainable Automation Practices 

In many industries, manufacturing included, sustainability is becoming a guiding principle shaping the way toward a greener, more efficient future. According to a recent report, the manufacturing industry in the UK was responsible for producing almost 80 million metric tons of greenhouse gas emissions in 2021, accounting for around 17% of the UK's total GHG emissions. This figure, while 40% less than in 1990, underscores the pressing need for sustainable practices. Globally, the manufacturing industry is responsible for 20% of all carbon emissions. As the global community increasingly works towards minimising our environmental impact and foster resource efficiency, manufacturers are using automation technologies to spearhead a transformative shift towards sustainable practices. 

In 2024, manufacturers are embracing green manufacturing practices with fervour, recognising the pivotal role they play in curbing environmental footprints and advancing sustainability agendas. From minimising waste generation to optimising energy consumption, green manufacturing prioritises eco-conscious processes across the production spectrum. Companies are integrating renewable energy sources, such as solar and wind power, into their operations to reduce reliance on fossil fuels and mitigate carbon emissions.

Central to sustainable automation practices is the relentless pursuit of resource efficiency and waste reduction. Automation technologies enable precise control over manufacturing processes, minimising material wastage and energy consumption. Innovations like predictive maintenance and machine vision systems not only enhance operational efficiency but also contribute to reducing downtime and optimising resource utilisation. 

In alignment with the global push for renewable energy adoption, manufacturers are integrating renewable energy sources into their production facilities. From solar panels adorning factory rooftops to wind turbines harnessing clean energy, these initiatives not only lower carbon footprints but also foster energy independence and resilience. 

Embracing the principles of the circular economy, manufacturers are reimagining product design and lifecycle management to minimise waste and maximise resource efficiency. Incorporating recyclable materials and designing products for disassembly and reuse are becoming standard practices, driving the transition towards a more sustainable manufacturing ecosystem. 

In response to mounting environmental concerns, governments worldwide are implementing stringent regulations aimed at reducing carbon emissions and promoting sustainable practices. Manufacturers are not only adhering to regulatory requirements but also proactively embracing sustainability as a core principle of their corporate ethos. This proactive stance not only enhances brand reputation but also fosters resilience in the face of evolving regulatory landscapes. 

With such a big effort being made towards improving sustainability and moving towards a carbon zero future, hiring is anticipated in these roles:
 

  • Sustainability Analysts – these professionals analyse data to identify opportunities for reducing environmental impact and improving resource efficiency across manufacturing operations. 
     

  • Renewable Energy Engineers – responsible for designing and implementing renewable energy systems, such as solar and wind power, to reduce reliance on fossil fuels and lower carbon emissions in manufacturing facilities. 
     

  • Environmental Compliance Specialists – these specialists ensure that manufacturing processes adhere to regulatory requirements and environmental standards, mitigating risk and fostering sustainability. 
     

  • Circular Economy Strategists – develop strategies to redesign products and processes for a circular economy, minimising waste and maximising resource recovery throughout the product lifecycle. 
     

  • Automation Systems Engineers – these engineers design, implement, and optimise automation systems to enhance operational efficiency, reduce energy consumption, and support sustainable manufacturing practices. 


Sustainable automation practices are at the forefront of manufacturing evolution in 2024, driving innovation, efficiency, and environmental stewardship hand in hand. By harnessing the power of automation for sustainability, manufacturers are not only safeguarding the planet for future generations but also unlocking new avenues for new growth and profitability. 

 

Remember 

In 2024, manufacturing is undergoing a profound transformation driven by automation. Despite challenges in 2023, the industry is rebounding with a focus on efficiency, innovation, and sustainability. From AI-driven automation to collaborative robotics, edge computing, and sustainable practices, the trends highlighted here are reshaping manufacturing operations worldwide. AI addresses critical challenges like supply chain volatility, while collaborative robotics enhances productivity and safety. 

Edge computing, digital twins, and sustainable automation practices are essential pillars for operational excellence and environmental stewardship, offering real-time insights and resource-efficient solutions. The roles outlined in this article, from AI engineers to sustainability analysts, reflect the growing demand for talent at the intersection of technology and sustainability. Companies prioritising innovation, sustainability, and talent development will lead the charge in the global marketplace. 

The trends in automation signify not just technological advancements but a shift towards a more resilient, sustainable future for manufacturing. By embracing these trends, manufacturers are driving growth and shaping a brighter future for generations to come. 

 

If you would like to discover how we can help you strengthen your automation practices and build out your team, head to the Hamlyn Williams contact page and get in touch today.   

 

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Rebekah Prime
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