The Manufacturer’s Complete Guide to IoT — Drive Efficiency with Embedded Intelligence

Manufacturers struggle to stay competitive in times when customer expectations are through the roof, the global supply chain is getting increasingly complex, and customization is a necessity. Now, manufacturers explore more innovative ways of solidifying their foundation in the marketplace.

Industrial Internet of Things is a way for manufacturers to transform operations and set digital transformation in speed. Industrial IoT uses a network of sensors to collect industry-wide data and opens up new avenues for businesses using insights gathered from that data.

The Bsquare annual industrial IoT maturity survey reports that 86 percent of respondents have already adopted IoT solutions, and 84 percent of them found those extremely effective. The survey proves the notion that IIoT adoption is increasing as more and more manufacturers shift toward advanced IoT applications with analytics and automation.

We explore the various factors driving the proliferation of IIoT in the manufacturing industry. You might notice that these factors roll into one another to create a giant reason why manufacturers are now more inclined toward IoT than they ever were.

• Automated Facility Management — IoT-connected sensors can monitor conditions such as temperature, humidity, vibrations, and more. With automated facility management solutions, manufacturers can now identify and maintain the ideal conditions for equipment and people to function at their best.
• Just in Time Manufacturing — Real-time data reporting facilitates JIT manufacturing, where processes can be (re)adjusted in real-time to reduce waste and optimize production time in sync with materials and raw materials.
• Enhanced Equipment Utilization — Industrial IoT helps manufacturers connect machines to the Internet. This interconnectivity offers insights into machine health and other critical indicators in real-time. Some of these KPIs are Overall Equipment Effectiveness (OEE) and Overall Process Effectiveness (OPE). With this data, manufacturers can identify and fix causes that might lead to unplanned downtime. Insights from this data highlight the need for preventive equipment maintenance and help increase equipment utilization. ITIF Research finds that monitoring machine utilization with IoT can improve manufacturing productivity by 10 to 25 percent, producing a global economic value of up to USD 1.8 Tn.
• Predictive Maintenance — Instead of offering a piece of equipment, manufacturers now offer an optimized experience. With predictive maintenance, companies now take preventive measures to enhance the health of their equipment before noticing any signs of defect or anomaly. Predictive maintenance eliminates process time, scrap, rework, and unplanned downtime. Deloitte reports that predictive maintenance solutions can slash costs by 40 percent and generate an economic value of USD 630 Bn annually by 2025.
• Cost Reduction — With the industrial Internet of Things, companies optimize resource use, manage inventory better, reduce machine downtime, efficiently use energy, and reduce overall operational costs and create new sources of revenue. Smart inventory management solutions allegedly save 20 to 50 percent of an organization’s inventory carrying costs.
• Making Global Possible — Centralized knowledge can help manufacturers standardize processes and keep the ball rolling. Data silos, and knowledge gained through years of experience, passed down to the coming generations orally but never captured/documented- are two of the most significant causes of inefficiency in manufacturing units. Since baby boomers are now retiring from the workforce as fast as 10,000 a day, manufacturers need to preserve knowledge now more than ever.
• Monitoring Employee Performance — Data gathered from sensors and other IoT-enabled devices can help organizations keep a tab on employee performance. With this data, they can identify gaps in productivity or efficiency, and take proactive steps to fill those gaps. Employee performance insights might show common inefficiencies in handling a certain class of jobs, which can be eliminated through skill training, for instance.

What Constitutes an IoT Initiative?

According to the ARC Advisory Group, there are four key components of the Industrial Internet of Things:

1. Intelligent Assets — These are connected things such as sensors, edge devices, controllers, as well as software and security components that are essential to fire up IIoT for any company. These devices come with intelligence and communication capabilities. These competencies can be added to legacy systems, too. Here are a few equipment and devices that enable IIoT:

• Sensors capture and relay data from assets, making it externally accessible using protocols and technologies for communication.
• Edge devices are hardware components that control and regulate the flow of information between two networks, serving as network entry and exit points. These carry on functions such as routing, transmitting, monitoring, translating, and storing data between two networks.
• IoT gateways are a kind of edge devices in a manufacturing setting.
• Embedded systems have their own computing capabilities including memory, processing, communication, and operating systems.

2. Data Communication Infrastructure — Intelligent assets within a digital manufacturing ecosystem need the Internet and other network technologies to be able to communicate. Since IIoT systems are often deployed on cloud infrastructures, storing, managing, and processing of data takes place using a network of remote servers rather than a local server.

3. Analytical Capabilities — Manufacturing companies cannot be satisfied with capturing the data that comes to them through sensors and other smart equipment. For them to truly leverage this data, they need analytics to spot patterns and make better decisions to improve their bottom line. Cloud-based analytics can lead to several benefits for manufacturers, including increased speed, reliability, flexibility, and reduced cost.

4. People and Leadership — An often overlooked component of the IIoT system is the people. People interact with the IIoT system and make decisions based on the insights they gather from data. It still remains a critical piece of the puzzle for manufacturers to onboard new talent to work on IIoT-enabled systems, or use in-house talent to grow through the transformation. When people are closely connected with machines, plant equipment, systems, and other personnel, quantified decision making follows and businesses reap the benefits of IIoT quicker.

The Simplified Roadmap to Implementing IIoT for Manufacturers

According to a survey, the toughest challenges in implementing IoT facing US enterprises include ROI uncertainty, data security and privacy issues, the unavailability of qualified employees, and integrating IoT with legacy systems.

The key to addressing these challenges is following a simple and straightforward strategy.

Define (Achievable) Goals

Identify the Key Performance Indicators and define the business case for your IIoT undertaking. IIoT projects should not be pursued to ride the popularity wave, but to address specific business problems such as improving machine utilization, quality of the produce, driving faster implementation and upgrade cycles, and so on.

Know what questions you want your data to answer before collecting any data through IIoT. Analyze, categorize, and summarize information on aspects you want to improve.

Create a Plan

Ask how you can collect the data you need and what technologies can enable you to harness it.

Evaluate the current state of connectivity in your enterprise. If you are looking to kickstart IIoT with legacy equipment, the process might look more intricate for you than for a manufacturer who uses systems that come with OPC or Ethernet connectivity.

Note down the several changes you will need to make internally in order to embark on the IIoT journey. And, make sure you keep in mind that each change incurs a cost in terms of money and time.

Prove There is ROI from the Effort

What value do you expect IIoT to create for you? Define the return on investment.

Be strategic in planning and approaching the question of ROI. Consider finding an area within your enterprise where you can demonstrate quick ROI with IIoT. Start with small steps and define a reasonable timeline, success metrics, a dataset to measure, and so on.

Simple is better. Resist the temptation to start with a complex initial setup, as that might drain your resources faster and leave you with little to address the real challenges.

Get Organizational Buy-in

Once you have the ROI of a successful proof of concept, pitch the project to the top-level management and stakeholders. Any business transformation requires changes in the culture- which already looks ‘comfortable’ to the entire enterprise.

Support and commitment across organizational hierarchy can be your key to success.

Scale up Implementation

As you see results from smaller projects and pilots, you will be more confident in scaling up your IoT efforts. Incorporate feedback from stakeholders on the PoC. As you move to the full implementation, have a high-level roadmap.

It is easy to get swayed by the daily humdrum and forget what mattered when you started. Keep clarity on the high-level objectives, link actions to vision, and stick to the timeline and cost preferences.

The Internet of Things can lead to measured success in a manufacturing setting. McKinsey maintains that IoT applications in manufacturing can generate USD 1.2 to 3.7 Tn in economic value annually by 2025.

How poised is your organization to leverage IoT?

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