» IoT and Smart Manufacturing

Smart Manufacturing: IoT and the buzz?

Complex manufacturing production plants and multi-unit organizations generate large amounts of information, which if not captured and acted upon in a timely manner by various key decision-makers along the chain of commands, can lead to costly breakdowns and delays.
Constantly evolving and more stringent iteration of the FDA and GMP regulation is consuming the manufacturing sector. The need to adhere to these FDA/GMP regulations, demand a colossal transformation in the way goods are manufactured especially in the Food & Beverages or the Pharma manufacturing sub-segments.Smart Manufacturing is no longer a nice to have option – it is increasingly becoming the general norm that more and more manufacturing operations are now adopting.
So what is involved in Smart Manufacturing and what role would an end-to-end IoT solution play in this?

Deliver actionable insights to drive real-time decisions

In its simplest definition Smart Manufacturing (SM) is ability to gather real-time information and use it to pre-emptively resolve production issues for a more efficient and agile operation. This necessitates mechanical engineering be inextricably linked with IT.
An integrated SM process extends the visibility from a batch-level to a unit-level so that at any given point of time the all line manager and key decision-makers can easily identify:

What it is; Which unit type is under production?
Where it is; Which step of production is it on?
In what condition it is; Is it under set parameters?

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A 3-step process

An end-to-end IoT solution integrates with the production process every step of the way to increase the overall process efficiency and deliver improved productivity and customer experience through secure, real-time operational intelligence.Smart Manufacturing maximizes value by super-charging the following 3-step process:
Gather Data: Collecting accurate information by enabling real time operational visibility into people and things becomes the base for developing an operationally efficient process. Heterogeneous devices from simple RFID chips to programmable intelligent sensors can be deployed through the plant floor and beyond to collect accurate data in real-time. Barcodes, RFID chips, GPS trackers, temperature sensors, are just some of the more commonly deployed devices within the manufacturing sector. These devices have the ability to gather information based on pre-programmed parameters. Most of these devices and sensors have inbuilt capability to transmit data securely using industry standard protocols (CoAP, LWM2M). A wide selection of wired, wireless (Wi-Fi, BLE,) and cellular (3G/4G and now 5G in very near future) enable ubiquitous connectivity, making it easy and efficient to transmit and receive data in near real-time and even instantaneously.
Analyze: Parsing through a large amount of data to identify anomaly, analyze it and infer intelligent insights is the next requirement to create an efficient operational process.
Clouds have played a catalytic role in advancing the adoption of SM options by the industry in general. Millions of connected devices equals several petabytes of data. The data must be stored before and after analysis. This is where a secure Cloud option becomes critical. Without the vast storage capacity that Cloud provides at an affordable cost – the benefits of SM could not have been realized by manufacturing industries within every level. Cloud also makes it easy to scale the operations by adding newer sensors/data collection nodes to the overall architecture.

Execution:Last but not the least is the automation of systems to drive real-time actions that can alter the overall outcome.This is the key area where Internet of things aka IoT arguably differs from Machine to Machine or the M2M. Where the sole purpose of M2M was to collect raw data and transmit it over to a secure location for human interjection for the alternation of the circumstances – the IoT solutions take it to the next level by enabling the automation of even the last leg.IoT ‘s automated problem resolution or course correction provides Smart Manufacturing the true path to improved operational efficiency and reduction of wastage and costly errors.
While there are several players, both named and newcomers, in the initial part of a SM process, very few have actually been able to address the most important final step for a fully automated operation.
Key reason why this obvious profitable option still remains elusive to most IoT dabblers is because it requires an in-depth understanding of not just the operational process and the expected outcomes, but also of the legacy hardware and software that characterizes the majority of manufacturing organizations. To truly impact this last bit of automation, the IoT solution must be able to fully integrate with the existing legacy processes. This is the deciding factor that will change the impact of IoT for Smart Manufacturing invariably over the next few years.