IoT Impact on the Manufacturing Industry (Part 2)

Continuing on from my last blog post, another example for IoT use in manufacturing would be for the asset management to distribute work orders and configurations to the tools or the different stages of production. And vice versa, calibration information can be fed back to the Enterprise Resource Planning (ERP) system to associate them to the bill of material (BOM). Big data and NoSQL technology is an enabler in this regard, as they can allow for the management of huge volumes of heterogeneous, multi structured data about the production process, from the data types discussed, to even images from AOI (Automated Optical Inspection) systems and other production modules. With recalls a concern point in global manufacturing, this can be an ally in the fight to keep costs down for manufacturing.

IoT can also have an impact is in intelligent edge devices and their use in improving supply chain optimization and modularity of manufacturing. Consider surface mount technology (SMT), where there is so many moving parts, calibration, types of technology used in the placement and verification of board level components. IoT sensors could be utilized to centralize SMT line asset management and to read calibration information via the factory WLAN. The asset management can form the link between the SMT tools and the ERP (Enterprise Resource Planning) and MES (Manufacturing Execution Systems) that oversee the manufacturing process.

A challenge that presents itself to the manufacturing industry is the ageing workforce, and this means that anything that speeds up the manufacturing process is critical. The advancement in mobile technology is a key enabler in ensuring that passing information to the shop floor becomes quicker, improving response time, visibility, and accessibility of operations. The recent advancement of wearables also will have an impact on enhanced visibility on the shop floor.

Building Blocks for IoT in Manufacturing

Business owners need to look at four technology elements that provide the foundation for smart manufacturing. These include (but not limited to):

• Security: IT security is a major obstacle to setting up smart factories. Operations managers need to make sure that necessary safeguards are built into the solution including security procedures such as physical building security, hardware encryption and network security for data in transit. Security and networking solutions must also be engineered to withstand harsh environmental conditions, such as moisture and temperature, that aren’t present in typical networks. Identity and authentication structures will also need to be updated to support such “things” as well as people.
• More Advanced Networking: Smarter manufacturing environments need a standardized IP-centric network that will enable all the devices/sensors in a plant to communicate to enterprise business systems. Cisco research states that only 4 percent of the devices on the manufacturing floor are connected to a network. A standard IP network also makes it easier to connect and collaborate with suppliers and customers to improve supply chain visibility. Manufacturers need robust networks that can cope with Radio Frequency (RF) challenges in the plant, harsher environmental conditions and need stability for transmission of alarms and real-time data processing.
• Big Data Analytics: While manufacturers have been generating big data for numerous years, companies have had limited ability to store, analyze and effectively use all the data that was available to them, especially in real time. New big data processing tools are enabling real-time data stream analysis that can provide dramatic improvements in real time problem solving and cost avoidance. Big data and analytics will be the foundation for areas such as forecasting, proactive maintenance and automation.
• Engineering Software Systems: Today’s IoT data is different than the data we use to operate our systems. It requires collecting a wide range of data from a variety of sensors. These software systems and models must translate information from the physical world into actionable insight that can be used by humans and machines. Toyota is using Rockwell’s software for real time error corrections in the plant. Toyota has minimized rework and scrap rates in its Alabama plant, which has resulted in an annual cost saving of $550,000.³

Building blocks for end-to-end infrastructure enabling manufacturing intelligence from the factory floor to the data-center (Intel) [4]

With IoT, IP networks and analytics, manufacturers can become more efficient, improve worker safety and offer new exciting business models. IoT will help manufacturers improve resource efficiency, safety and return on assets. Manufacturers that master this new dynamic will have a variety of new opportunities for revenue growth and cost savings.

References

3: How IoT will help manufacturing

http://www.industryweek.com/blog/how-will-internet-things-help-manufacturing

4: Industrial Optimization IoT (Intel)

http://www.intel.ie/content/dam/www/public/us/en/documents/white-papers/industrial-optimizing-manufacturing-with-iot-paper.pdf

IoT Impact on the Manufacturing Industry (Part 1)

“Industry 4.0” and “Smart Factory” are some of the terms used to describe the technological and social revolution that promises to change the current industrial landscape. Industry 1.0 was the invention of mechanical assistance, Industry 2.0 was mass production, pioneered by Henry Ford, Industry 3.0 brought electronics and control systems to the shop floor, and Industry 4.0 is peer-to-peer communication between products, systems and machines. It is clear that IoT will have a different impact statement depending on the application and/or industry, one that is of particular interest, given the emphasis on process, is Manufacturing. Compared to other realms such as retail and its intangible ways, manufacturing is about physical objects and how we can bring them to the consumer in a more efficient and automated way. The manufacturing landscape is ever changing, with automation through robotics the most recent enabler.

Challenges and Possibilities of IoT and Manufacturing ¹

Gartner analyst Simon Jacobsen sees five immediate challenges and possibilities posed by the IoT for the manufacturing industry¹.

1. CIOs and manufacturing leads will have to move even more rapidly

Jacobson says manufacturers have moved heavily toward individualization and mass customization as part of the luxury of connected products. But in order to enable that, you have to maintain alignment with supply management, logistics functions and partners to make sure all service levels are maintained: “I have to have knowledge of my processes and optimization of my processes at a hyper level, not just simply understanding at week’s end or at the end of the shift where I need to make adjustments and improve,” Jacobson said.

2. Security must be reimagined

A connected enterprise means that you can no longer simply physically secure the facility but should blend approaches of mobile and cloud-based architectures with industrial, control and automation, ensuring information is being managed. Jacobson says the challenge will be to merge the skills of engineers and process control teams with IT and more importantly, unify their disparate approaches to security.

3. IoT will create more visibility in process performance

There’s always been a form of automation and control in manufacturing, but implementing new business applications powered by IoT will allow you to connect devices to the factory network and know tolerances: “Being able to connect those dots and derive contexts of how processes are performing is absolutely going to be where the return on investment is coming from,” Jacobson said.

4. Predictive maintenance can generate revenue for OEMs

Asset performance management is of high value today. This is the ability to drive availability, minimize costs and reduce operational risks by capturing and analyzing data. Original Equipment Manufacturers (OEMs) have already started creating revenue by using IoT-enabled tools like predictive maintenance in order to guarantee uptime, outcomes and certain levels of performance for the customer: “When you guarantee these kinds of outcomes to the customers, you have to look at this from two different perspectives, how I monetize this but also how my customer monetizes this,” Jacobson said.

5. Production will play a new role in the manufacturing value chain

The boundaries between the physical and digital worlds are blurring. Chief Information Officers (CIOs) and manufacturing strategists can use the IoT, big data and cloud to redefine the role production plays in the manufacturing value chain. It no longer has to be restricted to being a cost center, and this has all to do with the new ability to not just accelerate but innovate on the factory floor. It’s the CIO’s challenge to keep pace with these new competitive changes.

Figure 10: Real Time Intelligence on the Shop Floor [2]

In my next blog post, I will continue this discussion on IoT and Manufacturing, giving further use cases, and outlining the building blocks for IoT in Manufacturing.

References:

1: Gartner Best Practices for IoT in Manufacturing

https://www.gartner.com/doc/2899318?ref=AnalystProfile

2: Building Blocks for a Smart Plant

http://www.mbtmag.com/articles/2014/10/manufacturing-transformations-building-blocks-future-smart-plant