The Connected Factory: A Guide to Scaling Industrial IoT for Manufacturers
If you started a coffee machine with your phone or your voice or have your household things connected to the internet, it is the Internet of Things (IoT). You have connected light switches, cars, home appliances providing efficient and safe experiences to millions.
Industrial Internet of Things (IIoT) is a branch of IoT engaged explicitly with the manufacturing industry. It connects industrial equipment and tools to increase speed, safety and make production facilities run smoothly at lower costs.
The usage of smart things has already reached critical mass and is now a staple for Industry 4.0. Experts believe that the Industrial Internet of Things (IIoT) will add 10% to the global economy in this decade.
Benefits of IIoT
Interconnectivity, data analytics, and process monitoring are a result of a connected environment. As IIoT-connected machines capture and communicate real-time data, operators, supervisors, and engineers see far-reaching benefits.
Improves prediction power
During downtime, connected sensors can pinpoint where the issue occurs and trigger a request by analyzing sound frequencies, vibrations, and machine temperature to indicate its working condition.
The manufacturer can predict when a machine will likely break down or enter a dangerous operating condition. In addition, sensors will provide insight into machine health and essential KPIs in real-time and highlight the need for preventive equipment maintenance.
A packaging materials company outfitted its production equipment with IIoT sensors and improved the overall equipment effectiveness (OEE) by 9%. By decreasing downtime, factories can take better advantage of the factory’s operating capacity.
Another use case is oil workers’ safety. When an oil well reaches a potentially high-pressure situation, operators will receive a warning to remove the pressure, otherwise a manual exercise. Sensors can monitor workers’ location during an emergency or evacuation.
Tracks assets and manages facilities
Equipment and finished products go into a massive inventory lot on a site that could be spread into three-quarters of a mile on each side, making finding anything an arduous task. IIoT reduces workers’ time in locating tools, equipment, and finished goods inventory significantly.
Workers do not have to spend time putting back tools where they belonged either. IIoT’s location tracking ability is akin to a connected fob with keys, making it impossible to lose.
Besides, the environmental sensors monitor vibrations, temperature, humidity, and other factors. They can detect conditions that negatively impact operations or cause wear and tear to equipment.
Allows disruption of enterprise business models
We believe that there will be a proliferation of high-value equipment, ranging from extending manufacturing robots to aircraft engines on a lease instead of selling. This equipment could have built-in sensors, marketed as both a product or a service.
The equipment owners will monitor equipment remotely and deliver maintenance, repairs, and upgrades, allowing companies to focus on manufacturing instead of worrying about machine health.
Allows knowledge sharing across plants
Data silos and knowledge gained over the years and passed down orally without standardizing or documenting are significant causes of inefficiency. Manufacturers must share knowledge. Not preserving knowledge will force future generations to re-learn.
Monitors behavior and processes
Managers gain data into identifying bottlenecks and areas of improvement. For example, management knows that employees will make mistakes or produce defective equipment.
The information into employee performance will allow process engineers to perform root cause analysis to determine improvement areas and use the data as a benchmark to measure progress, impacting business, saving cost, improving quality, and increasing efficiency.
Components of IIoT
IIoT consists of connected elements, which will generally include:
1. Intelligent assets
Intelligent assets comprise sensors, controllers, edge devices, application software, and security components. Each of these assets generates data and share information across the value chain.
Sensors provide new data from existing assets or incorporate new or existing machines accessible using standard protocols and communication technologies. Edge devices control data flow at the boundary between two networks, serving as network entry or exit points.
Edge devices, including IoT gateways, collect, process, and store data closer to endpoints to use network resources efficiently. Embedded devices, with their computing capabilities, including OS, memory, communications capability, work in concert with other devices within the system.
2. Data communication infrastructure
All the above assets require internet and other network technologies to communicate. IIoT systems are often deployed on cloud infrastructures like AWS to facilitate communications, which stores, manages, and processes data using a network of remote servers.
IIoT software analyses the data from all the devices and equipment, provides an interface for users to interact with the entire IIoT system, allows people to make better decisions, and improves their performance.
Cloud-based software lowers the total cost of ownership, enables greater reliability, speed, and flexibility.
People are an essential cog in the wheel because they interact with the IIoT system and make data and analysis-based decisions. Better data and powerful analytics tools allow better connection with IIoT devices for plant equipment and systems personnel to monitor.
Implementing IIoT: What Does It Take?
The IIoT market will grow to USD 1.1 Tn by 2028 at a CAGR of 22.8%, indicating growth potential. In 2020, the market size was at USD 308.97 Bn. Therefore, Vendors must mobilize quickly to ensure they position themselves for long-term success. Here are what it takes to do that:
1. Define your goals and objectives
What is the business case of your project? The management must have clear and measurable goals, and address specific business problems, like improving quality, drive faster improvement cycles, and more.
The management may know what areas to improve but need data to pinpoint them. If they have specific questions they want answers to, they could analyze, categorize, and summarize the improvement areas.
2. Elucidate a plan and identify measures of success
The management must next plan how they will collect the data and what technology to use. They must consider changes needed for the network infrastructures, such as installing Ethernet drops and running cables, a significant investment in time and money.
A plan will help the company gain cooperation from the company’s IT experts. After implementation, they must measure goals by KPIs and pre-defined measures of success.
3. Prove RoI with a Proof of Concept (POC)
The right strategy is to demonstrate a quick return on investment (RoI) on a small scale. Then, manage expectations with defined success metrics and a specific data set to measure with a specific time frame.
The experiment must answer the following questions –
- What is the RoI?
- What value does the technology create for the company?
4. Get organization buy-in and scan for talent
With RoI from POC, pitch to the management to influence a cultural change within the organization. Additionally, identify, hire, and retain IIoT talent that can thrive in the existing technology landscape.
5. Take risks and implement at scale
Take feedback about the POC from stakeholders and then implement the feedback. Finally, create a high-level roadmap, linking action to vision and providing a reference for timeline and cost.
However, companies may fear that it would meet their P&L requirements or hamper their existing products or services. IIoT experts must remove the management’s fear and encourage them to redesign the operating model that doesn’t break the bottom line.
Finally, there are diverse IIoT platform options, but companies must choose the right fit and approach it scientifically. The first step is to outline problems you intend to solve and decide the team.
The Road Ahead for Manufacturing with IIoT
The biggest disruptor is the cloud and the ‘machine learning models,’ which will open floodgates with highly affordable solutions that scale effectively and quickly. Additionally, 5G could supplant cable and fiber-delivered physical networks to enable a true IIoT revolution.
The use cases will roll out to smart warehousing and maintenance, transportation and freight monitoring, smart metering and smart grid, industrial security, asset tracking, and smart logistics, industrial heating, ventilation, and air conditioning, ozone, gas, and temperature monitoring, worker safety monitoring, asset performance tracking and management, remote field servicing, and remote maintenance.
The connected devices can receive data on how the product is used by customers onsite, enabling developers to respond to customer behavior with new features and software updates. Thus, a connected product-as-a-service enables new services based on customer insights.
Manufacturers can shift from an upfront capital expenditure to operating expenses reducing the risk to customers, making it easy for companies to sign new customers and reach new segments.
The product-as-a-service model allows more flexibility and tailored pricing, such as charging customers based on usage instead of fixed prices. Thus, companies can have a continuous relationship with customers centered around service, support, and quick resolution, critical to survival.
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