Global manufacturing activity has failed to show signs of growth for much of 2023. S&P Global’s gauge of worldwide manufacturing activity came in at 49.1 in September, below the 50 mark that separates expansion from contraction. China’s Caixin/S&P Global manufacturing PMI also fell to 49.5 in October, down from 50.6 in September.

As the sector looks to recover, rising bandwidth requirements, restricted access to applications and increased latency all pose hurdles to ongoing efficiency in manufacturing. Facilities have complex infrastructures, connecting multitudes of platforms and devices. Legacy hardware and software implemented by different integrators create a challenging ecosystem. The integration of Internet of Things (IoT) devices and other smart technologies has made manufacturing networks more complex and, consequently, more vulnerable to disruptions.

In recent research commissioned by OpenGear, “Measuring the True Cost of Network Outages”, nearly one in three (31%) of senior IT decision-makers globally said network outages had cost their business over $1.2 million over the past 12 months and one in six in total (17%) said it had cost them $6 million or more.

However, the impact on manufacturers from network downtime extends beyond direct financial costs. Efficiency in manufacturing is not just about maintaining a steady production rate; it’s also about the ability to quickly adapt and respond to changing market demands. Network issues can hinder this adaptability, causing delays in communication, data transfer, and decision-making processes. In an industry where time is money, these delays can be particularly detrimental.

In summary, the challenges of network downtime and efficiency in manufacturing are multifaceted, impacting not only the immediate production processes but also the broader operational dynamics of manufacturing businesses. Addressing these challenges is crucial for maintaining competitiveness in a rapidly-evolving industrial landscape.

To do this effectively, manufacturing organisations need a platform that ensures always-on remote access. Continuous connectivity is critical for supply chain visibility, IoT data collection and asset management.

Synergising AI and Smart OOB for manufacturing excellence

The combination of artificial intelligence (AI) and Smart Out-of-Band (OOB) management has the real near-term potential of revolutionising the manufacturing industry. By synergising these technologies, manufacturers can significantly enhance their operational efficiency and reduce network downtime, both of which are critical factors for maintaining a competitive edge.

The past year has witnessed a remarkable surge in AI growth, and this momentum is expected to accelerate, ushering in a significant impact on IT operational efficiencies. As a result, the new term or category of AIOps has been recently created. So, what is AIOps? Gartner defines AIOps as the marriage of Big Data with machine learning to create predictive outcomes that drive faster root-cause analysis and accelerate mean time to repair (MTTR). Add Smart OOB to AIOps and you have the most powerful combination of tools available that can deliver true Network Resilience.

AI plays a pivotal role in predictive maintenance, a technique that uses device visibility and data analytics to foresee equipment failures before they occur. This proactive approach can significantly reduce unplanned downtime in manufacturing, with Deloitte suggesting it can reduce equipment downtime by up to 50%.

But using AI for predictive maintenance is just the start. If you extrapolate the full use of AIOps it can provide better real-time operational analysis, which in turn could drive better network capacity planning, it can pro-actively improve network optimisation and ultimately drive the quality of experience of all network users. Network ‘uptime’ is not the only measure used anymore, the next evolution will focus on the provision of a seamless and consistent ‘user experience’; to any device, to any application and from location.

One issue that does need to be addressed is that many people have a very limited trust in AI and its potential impact on their lives, driven in part from a lack of understanding. Like all transformational technologies, AI has the ability to be used for good or bad. In the context of the Networking environment the use of AIOps has huge potential for delivering good by providing intelligent, actionable insights that drive a higher level of automation, collaboration, and user experience.

The skills dimension

At the same time, AIOps provides a way both of addressing the current skills shortage in manufacturing and also of complementing the day-to-day activity being carried out by the existing workforce. Far from signalling job elimination, AI streamlines server monitoring and resource allocation, allowing human operators to focus on the strategic facets of the manufacturing process. This transformative power opens avenues for professionals across the sector to evolve and adapt their skill sets.

While technology advances, the human-centric approach to innovation remains crucial. As the next generation of tech-savvy employees enters the workforce, businesses must ensure their technology deployments keep pace with the latest developments, especially amid a growing skills shortage.

The rise of Smart Out-of-Band in tandem with AI

Smart Out-of-Band (OOB) management complements AIOps by providing a reliable, dedicated ‘always on’ backup communication channel for network devices. In the event of a primary network failure, Smart OOB allows for remote troubleshooting and recovery, ensuring that the manufacturing processes remain uninterrupted. This capability is crucial in a landscape where even a few minutes of downtime can result in substantial financial losses.

Furthermore, the combination of AI and Smart OOB enables more efficient resource allocation and better decision-making. AI algorithms can analyse vast amounts of data from network devices, providing insights that can be used to optimise production processes and resource utilisation. Meanwhile, Smart OOB ensures that these AI-enabled systems remain connected and functional at all times, even during network disruptions.

In essence, the synergy between AIOps and Smart OOB in manufacturing leads to a more resilient, efficient, automated and adaptable production environment. This integration not only addresses the immediate challenges of network downtime and efficiency, but also paves the way for future innovations in the manufacturing sector and beyond.

Empowering network teams for the future AI’s integration into manufacturing operations is transforming roles and skills, paving the way for a future where technology and human expertise coalesce, offering unprecedented possibilities. Embracing this
evolution presents an opportunity to redefine network management in the digital age. With AI’s increasingly transformative role in managing and monitoring networks, the broader industry stands at the cusp of a revolution, intertwining innovation and resilience with human expertise to unlock vast possibilities.

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