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The term Internet of Things was first coined in 1999 by Kevin Ashton, cofounder of MIT’s Auto-ID Center, in a presentation for Proctor and Gamble. In his presentation, Ashton outlined what would be the core of IoT: letting computers efficiently and accurately control physical systems in a way humans could not.
In more technical terminology, IoT is an interconnected system of both mechanical and digital computing devices which uses sensors in machines, animals, and even people to create unprecedented amounts of detailed data on important systems in order to make them better. Computers can then transfer this data over a network without any human intervention and communicate with other machines or human operators to make task easier and more efficient.
The ‘thing’ in IoT is defined as a physical object that can be assigned an IP address and given the ability to send data over a network. This can be the insulin regulator for a diabetic individual that tells it's used when their blood sugar is low, a door lock that can be activated remotely from a phone, or a tire that will alert the car’s driver when pressure is low.
Thanks to IPv6, the number of possible IP addresses is practically infinite and advancements in technology mean that sensors are becoming smaller and cheaper all the time. This sudden accessibility of transmittable data translated into new ways for businesses to monitor their machines, and the Industrial Internet of Things (IIoT) was born.
Below is an overview of what IIoT can do, how it can be implemented in your company, and why it will continue transform food manufacturing for years to come.
While previously entirely separate, information technologies (IT) and operational technologies (OT) are brought together in a radically new way under IIoT. This provides new challenges both for IT and OT, revealing the need for a less segregated, more generalized view of providing service in an IIoT setting.
For the individual IT team, IIoT brings up issues of what would happen should a system error occur. Due to the interconnected nature of IIoT, this could result in downtime at best and employee injury or bad product reaching the customer at worst. Additionally, if old machines run different data architectures, integration can be very difficult.
The individual OT team sees many of the same problems, but from a different perspective. Cloud-connected machines might open a company up to a new kind of corporate espionage. Hackers in an unprotected system could override safety and quality control protocols, harming workers and product, or steal sensitive machine data.
To protect against these new threats on both sides, new solutions must be formed with a combination IT/OT task force. This team can counter the new threats in IIoT by taking the following steps:
Depending on the needs of individual mechanisms within the company, IIoT allows for three levels of connectivity:
With monitoring, data may be collected from machines and shown directly to an operator without going through computer analysis first. This centralizes data silos without additional structures.
Optimization allows computers to process data and use advanced analytic software to provide actionable insights on production. This allows for human workers to use the information gleaned from the computers to manually increase efficiency and productivity.
Finally, automation allows smart factories to self-regulate without any human interaction. This allows quicker responses, and powerful reductions in waste and downtime.
These three levels can be mixed and matched based on a company’s needs and preferences
With the wide range of sensors available and the even wider range on software solutions to parse data, the possibilities of IIoT in the food industry are nearly limitless. Implementing IIoT in your factory will transform your food manufacturing network on every level, from raw materials to inside the factory, to delivering a finished product to clients and consumers.
IIoT can be used to ensure sufficient stock in inventory and automatically order new supplies as they’re needed. Either optimized or completely automated, this innovation can reduce waste by tracking demand and ordering raw materials as they are required. Automatically integrate schedules and orders with production speed to minimize downtime and increase production efficiency.
Sensors can give feedback to engineers and even machine manufacturers on the amount of wear or damage happening to internal components. Predicative software allows workers to know when maintenance is needed before a machine breaks and eliminates the need for routine checks, reducing downtime on both counts.
Using IIoT, factories can assess the quality of raw materials, mid-process goods, and finished products to prevent flawed product from reaching consumers. This helps eliminate the need for recalls, and helps engineers and managers detect faults in production to continuously improve the operation.
A fully integrated facility also means utilizing IIoT to protect staff. Key safety Performance Indicators (KPIs) like injuries, illness, and property damage can provide actionable insights to increase employee safety and prevent company losses.
IIoT can help companies conform to environmental guidelines automatically by digitally tracking waste and energy usage. This means fewer resources need to be used to meet regulations, reducing expenses.
Goods can be damaged while en route to a client, and IIoT has solutions for that, too. Sensors in trucks can detect bumping and degradation of packaging and products. By matching this to use patterns among various customers, packaging can be reengineered to deliver the best product with the lowest cost.
New vehicle-to-vehicle (V2V) technology is allowing trucks to communicate closely throughout the entire delivery cycle, allowing for new resource-savings techniques. The possibility of close tailgating can greatly reduce fuel expenses, as can tracking traffic lights to prevent full stops on the road.
The food manufacturing industry requires speed and volume to be profitable. The powerful analysis and optimization tools IIoT offers will allow machines to self-regulate and interact with other machines. Data no longer must be parsed and sorted by workers to create actionable insights, but can now be leveraged immediately in production.
A Retiring Skilled Workforce
Most current skilled workers in the food manufacturing industry are baby-boomers now nearing retirement. IIoT can help companies combat the pain of this turnover with powerful new tools for job training.
In a global economy, the web of raw materials, production, and distribution can be difficult to effectively visualize and plan. IIoT provides advanced data processing to plan supply roots and inventory so companies can make better, faster decisions about their business
Transitioning to a data-driven company will require a new kind of culture centered around the fast-moving nature of IIoT. New departments and jobs will be needed to handle the massive amounts of data. Data officers, scientists, and engineers will need to join the management to effectively use the new technology for maximum benefit.
With smart, connected machines and advanced software reducing the need for constant monitoring and routine maintenance, many of the old jobs will no longer be needed. But instead of firing these workers, retrain them to be problem solvers who use the new data to maximize factory productivity. Their knowledge of the system will help with a smooth transition to a data-driven workplace built on the idea of continuous improvement.
New architecture will also need to be prepared so the data can be easily stored and distributed. Cloud-based analysis will make it both easy and necessary for multiple locations to share the status of their machines, so best practices can quickly be implemented across many factories. Finally, IIoT on every level of the supply chain will create a new kind of vertical visibility for companies, allowing every aspect of production to be optimized for maximum profit and minimum waste.
A fully integrated food manufacturing network will reduce downtime, alert workers of maintenance needs, and provide greater control than ever over quality control both in processing and during packaging and distributing. But to enjoy the full benefits, all data processes must be standardized in all parts of the company.
Image Courtesy Boston Consulting Group
While it seems obvious to upgrade to IIoT as quickly as possible, many companies that rush experience a burnout and only achieve partial implementation or none at all. IIoT is a big investment with even bigger payoffs, so it is important to take the necessary steps when introducing it to your company.
Start with a small proof-of-concept project that will provide the momentum to carry a full transformation. Getting an easy data collection solution connected to a few key pieces of machinery can be a great way to PoC. This project should have a high chance of success, give rapid returns, and be highly visible to upper management. However, it is important it does not interfere too much with existing infrastructure, as it takes time and planning to fully integrate.
After a successful pilot, high priority projects can be identified for conversion, and a larger plan can be created for full-company restructuring. Investment can begin in advanced analytic software that will drive the third stage.
Change will begin to speed up and new positions and procedures will be needed to accommodate the new systems within the company. Soon, the whole operation will be interconnected and optimized in an easy viewable format.
Due to the incredible flexibility of sensors, the possible applications within factories and everywhere along the production line are practically unlimited. The only question now is how to best use this available data and turn it into actionable insights that benefit the company.
The food industry requires careful monitoring of all systems to work to be profitable. Balancing inventory with demand, ensuring consistent quality, and maintaining machine conditions are only a few of thousands if mini systems and processes that must work perfectly. IIoT data from all these systems can be centralized and put where it’s needed to allow for continuous improvement in food manufacturing.
"Hi, I'm Carole. I am a Data Scientist who has a background in industrial engineering. I have experience in performance analysis and operations management. In my day-to-day functions, I aim to always give meaning to data to help the manufacturers make smarter decisions."
Data Analytst - Worximity
"Hi. I'm Adrian. I manage Project deployments, customer training and value-added data analysis using my experience as a project engineer for different types of manufacturing operations, focusing on the client’s IIOT platform onboarding."
Customer Success Engineer - Worximity