Data: The Key To Unlocking The Value Of IoT In Manufacturing

Data: The Key To Unlocking The Value Of IoT In Manufacturing

2020 will be a big year for manufacturers. Deloitte predicts that, for the first time ever, Malaysia, Vietnam and Indonesia will break into the top 15 nations on manufacturing competitiveness, joining China, Japan, India, South Korea, Taiwan and Singapore. To realise this, APAC manufacturers will need to seize the Internet of Things. By Rick Scurfield, President, NetApp Asia Pacific.

Manufacturing is expected to be a huge driver of Asia’s economy in the future. Deloitte forecasts that by 2020, 10 out of the 15 most competitive manufacturing countries will be from this region. They include China, Japan, India, South Korea, Taiwan, Singapore, Vietnam, Malaysia, Thailand and Indonesia.

Why? Because Asian manufacturers are increasingly moving away from traditional manufacturing to advanced or smart manufacturing to address labour shortages and increased disruptions brought by advancements in technology. Leveraging the Internet of Things (IoT) by connecting their machines, systems and products – which are traditionally siloed – through networked sensors is one way of doing so. IoT enables manufacturers to improve operational efficiency and gain competitive advantage.


Predictive Maintenance

An apparel manufacturer, for instance, could use a combination of sensors, data and analytics to monitor the performance and operating environment of its production machines and take preventive action before any malfunctions. With this predictive maintenance capability, the manufacturer can reduce cost and time loss due to unexpected downtime and production outages. In a connected factory, IoT provides real-time insights across the production line. The manufacturer can quickly identify production lags and adjust to meet production orders.

Since the value of IoT lies in data, a data management strategy is central to the success of IoT projects. It should cover five areas:

  1. Collect, which involves capturing sensor data and making it transportable.
  2. Transport, which focuses on ensuring data from connected things are securely and reliably transferred to the data centre.
  3. Store, which entails storing the sensory data and making it available for analysis.
  4. Analyse, which comprises of the analysis of sensor data.
  5. Archive, which looks at cost-efficient, long-term archiving of sensor data.

Manufacturers also need to ensure their data management strategy covers both data at the core (ie: data stored in a data centre) and data at the edge (ie: data generated at the device and machine sensors). In the former, all collected data is first sent to the data centre to be centrally stored before it is analysed. This is useful for analysing data retrospectively.

As for the latter – which is also known as edge computing – the connected device partially filters, analyses, and makes initial decisions based on the data it generates. A connected robotic arm in a production line, for example, can collect data on its performance, filter out the unimportant information, and only send alerts to the operator if there is an anomaly, such as overheating or parts failures. To enable edge computing and real-time analytics, manufacturers will need to leverage industrial PCs with built-in flash solid state drives. Since machines in a production line usually work with large magnets that impair mechanical hard disks, manufacturers should consider using flash-based storage when embracing IoT.

In addition, a good data management strategy should ensure that the same data management tools and processes can be used by manufacturers regardless of where data resides. As manufacturers increasingly adopt hybrid cloud for reasons of flexibility, they will need to have a uniform data format to be able to easily combine data from different environments for analysis.

Advanced Manufacturing

Moving towards advanced manufacturing might seem daunting as there are various things to address – especially from a data management aspect. One way of reducing this complexity is by using solutions that can unify IoT data to make it available to workloads or applications regardless of architecture and platform. Eliminating data silos and having the ability to access data wherever needed helps increase efficiency, as well as accelerate innovation for manufacturers.

The future of manufacturing in Asia Pacific (excluding Japan) will be built around smart and connected technology. IDC predicts that by 2021, manufacturers in the region will collectively spend around one-third of their total investment on IoT. But it is important for Asian manufacturers to remember not to jump on the IoT bandwagon because it’s a popular thing to do.

First and foremost, they will need a future-proofed data management strategy that allows them to effectively harness data that their connected devices produce. Only then will they will be able to use IoT to monitor the pulse of their business and make well-informed decisions to drive it forward and past competitors.

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