Rivoluzionare la produzione: l’ascesa e le sfide dell’IoT industriale in un mondo post-pandemico

Introduction

About two years ago, McKinsey’s survey of business leaders revealed a startling fact: 92 percent of them acknowledged that their existing business models were unfit to endure the digital transformation. At that time, the thought of adapting to the fourth industrial revolution or planning for the implementation of IoT solutions was daunting. Challenges were abundant, and the market seemed far from ready.

Fast forward to the pandemic era, the landscape has changed dramatically. Industrial IoT (IIoT) has burst onto the scene as companies seek to reduce human intervention on factory floors for safety and efficiency. The Japanese recorded a 13 percent growth in the export of robotic solutions, while Chinese robot production saw a 14 percent rise in August, a pattern that echoed across the Eurozone.

Current IoT trends in manufacturing

The current demand for IoT in manufacturing is fueled by COVID-19 concerns, productivity requirements, and a tighter regulatory environment. Companies are now looking past the initial barriers of IoT. By diversifying their services, innovating their products, and adopting better business models, they aim for growth.

The economic shift towards lower-cost sensors, connectivity, and cloud hosting is playing a significant role in promoting IoT growth in previously prohibitive areas.

Increasing affordability

The discussion around AI/ML, Deep Learning, Fog/Edge, 5G, and more is amplifying the innovative use cases for IIoT. But Rob Mesirow, Principal at PricewaterhouseCoopers, recognizes a fundamental trend that will act as a catalyst in IoT growth: cost reduction.

He stated, “Cost has been a tremendous barrier in IIoT feasibility. We are now seeing LPWAN, like LoRa, Sigfox, NB-IoT, and LTE Cat-M, as essential in reducing costs.” He envisioned countless more connections at lower costs, transforming business cases and ROI. “Connectivity dropping from $10-$20 to $1 per month justifies the business case,” he added.

Overwhelming data

The expanded use of IIoT devices is set to produce enormous amounts of data, forming the backbone of the fourth industrial revolution. Insights from this data will drive better business decisions, but as Alex West, Senior Principal Analyst for Industrial Technology at OMDIA, stated, “You must have the capability to collect the data first before investing in AI for analytics.”

5G, edge computing, and AI are attracting attention. Intel believes 5G will revolutionize industrial manufacturing, while edge technology will solve latency, bandwidth, reliability, security, and privacy issues.

Technological challenges of IoT in manufacturing

Despite advances, challenges persist in IoT deployment. West identified three main obstacles: retrofitting legacy equipment, cybersecurity, and skill development. These challenges have been magnified by the rapid response required by COVID-19.

Retrofitting legacy equipment

Manufacturing facilities often house machines over 15 years old, not designed for connectivity. The dilemma of retrofitting or upgrading these machines for data collection and analysis is significant.

Cybersecurity problems in IoT

The increasing connectivity brings a heightened risk of cybersecurity breaches, an issue now faced by a third to half of manufacturing companies in recent years. Dealing with cybersecurity challenges in IoT has become vital for many businesses.

Preparing the workforce

Technology may be the driver of IIoT, but people are equally crucial. It involves changing processes and encouraging the existing workforce, often set in their ways, to embrace new technologies.

Non-technical IoT challenges hurting the industry

Mesirow pointed to additional non-technical challenges. Validating ROI on significant capital investments in industrial automation can be problematic. The lack of integration in many IoT solutions, known as “siloed point solutions,” limits their effectiveness. Moreover, the need for an operating model that takes automation into account is essential, lest implementations fail to achieve their goals.

Conclusione

The manufacturing sector’s implementation of IoT is accelerating, but several technological and non-technological challenges need industry collaboration to be resolved. Education, integration with legacy systems, innovations in edge and deep learning, and developer accessibility will propel the growth of IIoT even further.