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Winning with IoT

In IBM Institute study, manufacturing innovators share ways they make data work.

Manufacturers face challenging business landscapes as industries converge, data proliferates and virtually everything becomes interconnected. New digital companies are establishing themselves in traditional markets, and   changing customer expectations are driving established companies to expand into new areas.

As they ramp up their performance, market leaders in manufacturing are capturing numerous forms of data from a variety of interconnected devices. Applying intelligence to that deluge of data allows them to develop more personalized customer services and experiences, transforming their brand and opening up new opportunities.

The opportunity is vast. Gartner has predicted that 2019 will usher in the deployment of 20.4 billion Internet of Things (IoT) devices, in a market that statista forecasts to be valued at more than $1.7 trillion dollars this year.

According to our IBM Institute of Business Value study, which focused on interviews with 271 industrial products manufacturing leaders (automotive, aerospace & defense, chemical and petroleum,electronics, industrial machinery manufacturers, tools, lumber production, construction) from multiple countries, visionary leaders take a long-term approach to an intelligent IoT strategy. They have the highest levels of IoT adoption and use a broad range of internal and external data to innovate their products or services and design new customer experiences.

These manufacturing market leaders share three common approaches:

Create an IoT infrastructure that can scale. To create this kind of solution, market leaders establish an IoT platform that can accommodate the growth in connections between products and services, increasing network complexity and exponential data growth. These types of platforms are typically cloud-based and combine device connectivity management software, data storage or data lakes and analytics services or insights. They can support billions of sensors and quickly process and route data to endpoints and to other devices.

For example, one global steel producer used an IoT solution for wearable worker safety. Data is collected from sensors embedded in helmets and wristbands. If there’s a threat to physical safety or if safety procedures are not followed, the technology delivers real-time alerts to employees and their managers, helping them take preventative action.

Invest in emerging technologies. Visionary manufacturing leaders are also likelier to invest, on average, more extensively in foundational technologies—such as IoT, mobile and cloud—than their average peers. They express a significantly greater commitment to future investment in emerging technologies, such as robots, and AI and machine learning.

The combination of these foundational and emerging technologies is a set of capabilities that can extend efficiency, speed and value across their businesses. For example, AI-based analysis and response is required to efficiently process the vast amounts of real-time data that stream from IoT devices. Additional benefits include the potential to increase throughput and uptime or decrease risk by analyzing machines, predicting outages and handling equipment repairs in real-time.

Integrate AI with IoT. With the addition of AI and machine learning, manufacturing industry leaders are realizing the full benefit of IoT across their business. AI systems can help predict and identify impacts and then recommend actions to improve production. For machine maintenance, AI can identify anomalies, assess their criticality, determine their root causes and help maintenance technicians correctly perform repairs.

Where can a manufacturing company start? Our research shows that market leaders typically establish a clear strategy to identify business problems that AI and IoT technologies can address, then articulate the expected benefits. Machine owners might implement IoT to help improve operations across fleets or facilities to reduce risks and increase ROI. At the same time, they keep their employees well-trained on the latest data analytics techniques and work carefully to establish the data infrastructure and determine the interplay between IoT and other foundational and emerging technologies.

For instance, by linking existing mobile apps with IoT, companies could create virtual shields to protect operators. They could then check employees’ alertness, hydration levels, proximity to dangerous equipment and environmental conditions (such as temperature or hazardous gases).

Market leaders execute their intelligent IoT strategy by establishing an open, scalable platform that leverages the broadest range of internal and external data available. This could include audio, video, weather, text and sensor data that can all be combined to create a new customer experience, product or service. For example, farm equipment manufacturers are combining intelligent machine data with weather data and crop pricing to optimize farm performance. Other companies use sensors, meters, actuators, GPS and other devices to report on shipping containers, trucks, products and parts. This real-time connection across an extended value chain can help them easily coordinate disruption response.

Ultimately, these actions are helping manufacturing companies reinvent their businesses by improving operational efficiency; introducing new products, services and revenue streams; and discovering new opportunities.

Spencer Lin is the Industrial Products and CFO lead for the IBM Institute for Business Value.
 

 

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