| Written by Christian Aadal
What is IIoT, and how does it relate to manufacturing?
Industry 4.0 represents a vital segment of the ongoing industrial revolution, characterized by an expanding network of digitally interconnected smart devices, equipment, and physical objects. Kumar and Iyer suggest that it highlights the adoption of the Industrial Internet of Things (IIoT) in manufacturing processes. Industrialists and manufacturers are actively participating in this shift by merging both new and existing Information and Operational Technologies (IT & OT). As a relatively new concept for industries, IIoT offers substantial opportunities for enterprises to enhance safety, productivity, efficiency, and cost-effectiveness (1).
The Industrial Internet of Things (IIoT) represents a transformative wave in the landscape of manufacturing technology. At its core, IIoT is about the interconnectivity of industrial machines and devices integrated through advanced communication technologies and software. This integration enables a level of automation and data exchange that was previously unattainable, leading to more efficient, reliable, and intelligent industrial processes.
IIoT is a complex set of technologies:
- IIoT involves embedding sensors, software, and other technologies into industrial equipment.
- It facilitates the collection, exchange, and analysis of data, enhancing machine-to-machine (M2M) communication.
- The core concepts include connectivity, automation, machine learning, and real-time data analytics.
Technological Foundation of IIoT in Tire Manufacturing
The Industrial Internet of Things (IIoT) in tire manufacturing relies on a sophisticated technological foundation, which is essential for its successful deployment and effectiveness. This foundation comprises several pivotal technologies, each playing a crucial role in realizing the potential of IIoT in the tire industry.
Central to the foundation of IIoT is cloud computing. Cloud platforms serve as the backbone for data storage, processing, and analytics. They offer the scalability and flexibility needed to handle the vast amounts of data generated by tire manufacturing processes. Cloud computing enables manufacturers to access and analyze data from anywhere, facilitating better decision-making and more agile responses to changing conditions.
Big Data is another critical element. Tire manufacturing generates a tremendous volume of data from various sources, including machine sensors, production lines, and quality control systems. Big Data technologies are employed to handle, process, and analyze this data. This analysis leads to actionable insights, allowing manufacturers to optimize production processes, improve tire quality, and reduce waste.
Artificial Intelligence (AI) plays a transformative role in IIoT. In tire manufacturing, AI algorithms are used to interpret the data collected, make sense of complex patterns, and predict outcomes. This includes predicting equipment failures (predictive maintenance), improving quality control through defect detection algorithms, and optimizing production schedules for maximum efficiency.
Finally, cybersecurity is an integral part of the IIoT infrastructure. As tire manufacturing facilities become more connected, the risk of cyber threats increases. Robust cybersecurity measures are essential to protect sensitive data and ensure the uninterrupted operation of manufacturing systems. This involves securing data transmissions, protecting cloud and on-premise systems, and ensuring that all components of the IIoT ecosystem are safeguarded against potential breaches.
In addition to these core technologies, the role of sensors in tire manufacturing cannot be overstated. Sensors are the eyes and ears of the IIoT, collecting real-time data from various points in the manufacturing process. This data is then transmitted to cloud platforms for processing and analysis, providing manufacturers real-time insights into their operations. The integration of these technologies forms the crux of IIoT in tire manufacturing, driving innovation, efficiency, and quality in the industry.
The Shift to Smart Manufacturing with IIoT
According to Yang et al., the contemporary manufacturing sector is embracing advanced technologies such as the Internet of Things (IoT), big data analytics, cloud computing, and cybersecurity. These investments are driven by the need to manage complex systems, enhance the visibility of information, boost production efficiency, and secure competitive edges in the global marketplace. Such technological advancements are fostering the emergence of smart manufacturing, defined as cyber-physical systems that seamlessly integrate physical manufacturing enterprises with their virtual counterparts in cyberspace. The successful exploitation of these cyber-physical systems largely hinges on developing innovative methodologies within the Internet of Manufacturing Things (IoMT) to harness data for engineering breakthroughs (2).
The Industrial Internet of Things (IIoT) heralds a significant shift in the manufacturing landscape, steering it away from traditional methodologies toward what is now known as 'smart manufacturing.' This transition is characterised by a profound change in how manufacturing processes are conceived, executed, and maintained, leading to a more automated, efficient, and intelligent production environment.
Central to this shift is the move towards automation. IIoT enables the integration of advanced machinery and robotics into the manufacturing process, reducing the reliance on manual labour. This automation is not just about replacing human hands; it's about enhancing the capabilities of the manufacturing process. Machines equipped with IIoT technologies can perform tasks with greater precision, consistency, and speed, leading to increased productivity and output.
Improved operational efficiency is another cornerstone of this shift. With IIoT, every aspect of the manufacturing process can be monitored and optimized in real-time. This includes everything from the supply chain and production line to energy consumption and waste management. By leveraging data analytics and machine learning, IIoT provides insights that help in fine-tuning processes, reducing downtime, and minimizing inefficiencies.
Moreover, the shift to smart manufacturing entails a significant reduction in human intervention. While this doesn't imply the elimination of the human workforce, it does mean a reorientation of human roles. Workers have moved away from repetitive, labour-intensive tasks to more strategic, analytical, and supervisory roles. This transition not only helps in reducing human errors but also in enhancing job satisfaction and safety.
In essence, the advent of IIoT in manufacturing is not just an upgrade of technology; it's a complete rethinking of how manufacturing should be conducted in the modern era. It promises a future where factories are more adaptable, efficient, and intelligent, paving the way for a new era in industrial production.
In the context of tire manufacturing, IIoT's relevance becomes particularly significant. The tire industry, with its complex and resource-intensive processes, stands to gain immensely from the efficiencies and insights of IIoT technologies. As we delve deeper into this article, we will explore how IIoT is specifically revolutionizing tire manufacturing, from raw material handling to final product testing and distribution.
WHAT CHALLENGES DO TyRE MANUFACTURERS HAVE?
The shop floor logistics necessary are complex and prone to human errors. Getting the right material, to the right tire building machine, at the right time can be a hassle. Manual bar code scans are still common practice, yet outdated, costly and not well suited for a First Expired First Out (FEFO) based production.
It is common practice in tyre manufacturing to load raw materials onto material carriers (or bobbins) at the so-called cutting machines, to store these carriers in storage locations and to transport the right carriers to the staging area of a tire building machine where the right carriers need to get inserted into the matching slots of a tire building machine.
In a large-scale production environment with multiple storage areas on several floor levels, thousands of material carriers and hundreds of cutting and tire-building machines, production logistics becomes a challenge aggravated by keeping control of the FEFO principle.
An unintended violation of the FEFO principle can lead to perished raw materials. Long search times for specific material carriers reduce labour productivity and increase the risk of perished goods. One missing carrier at the staging area – or just a forgotten scan of a carrier – impedes the start of the production order, reducing machine utilisation and labour productivity. And finally, the wrong material inserted into the tire-building machine results in a drop in profitability.
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HOW CAN TyRE MANUFACTURERS IMPROVE THEIR KPIS?
In order to reduce production costs, tyre manufacturers must increase machine utilisation, reduce scrap of raw materials, eliminate production errors of the final product and increase labour productivity.
Any IIoT-based solution must focus on the whole process, from loading raw material onto a material carrier (or bobbin), managing the storage and staging areas, as well as the insertion of carriers into the tyre-building machine.
Asset Agent is an efficient RTLS solution that solves all these issues: Every carrier gets outfitted with a battery-powered device – a so-called transponder – which enables the Asset Agent application software to identify, locate and communicate with every single material carrier at any given location in the production plant (see also: Automatic identification for optimised manufacturing). The solution scales up to thousands of transponders in one plant and works outdoors if required.
The Asset Agent server application offers standard interfaces to ERP systems (e.g. SAP Extended Warehouse Management – EWM) as well as other production and material flow management systems for a seamless integration into existing IT infrastructure.
HOW DOES ASSET AGENT WORK IN DETAIL?
When the raw material gets loaded onto a carrier at the cutting machine, Asset Agent checks via a patented wireless location technology if the carrier/material association is correct and provides immediate visual feedback to the worker via a red-yellow-green LED indication integrated into the transponder. The carrier can be moved to any storage location, allowing chaotic storage because the Asset Agent always knows its position with unmatched precision, also in a metal obstructed production environment.
The integrated LED indication serves as a pick-by-light system when a worker must find a specific carrier in the storage area – finding instead of searching is the design principle of Asset Agent. The carrier gets dropped onto the staging area and Asset Agent communicates its location automatically to the ERP system to complete the transport order and assigns material to individual building machines. Finally, while the carrier is pushed into the tire building machine, Asset Agent : Green for everything is ok, yellow for the right material yet the wrong batch and hence a violation of the FEFO principle, and red for the wrong material.
HOW ASSET AGENT IMPROVES YOUR KPIS
The entire tyre-building process becomes immune to human errors without any user interaction, therefore eliminating manual barcode scans. Every communication with the user is based on a globally established communication standard – a simple three-colour traffic light system – that doesn’t require any training.
Carrier search times are reduced, scrap due to perished raw material is abolished while machine utilisation and labour productivity go up. All in all, this leads to an increase in tyre output volume of up to 3% without investment into additional tire-building machines or more personnel.
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ASSET AGENT IS AN INDUSTRIAL-GRADE SOLUTION WITH A COMPELLING ROI
Used in production for many years in tire manufacturing plants across the globe, Asset Agent can be installed in any existing infrastructure, with the transponders providing an IP 65 rating. With its standard Power over Ethernet (PoE) and out-of-the-box interfaces to all major ERP systems, seamless integration into existing IT infrastructure is guaranteed. With a battery lifetime of up to 8 years, depending on the use case, only minimal hardware maintenance is required.
Asset Agent is designed for automated health checks of all infrastructure components, including the transponders, and integrates with network, server and log monitoring software such as Nagios, PRTG Network Monitor, Solar Winds and others. Even the battery exchange could be managed proactively by Asset Agent in connection with the plant’s PMS system to minimize the effort for plant maintenance personnel.
The initial investment costs are proven to have a compelling payback period of less than one year.
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Sources:
(1) Kumar, A.S.; Iyer, E. (2019): An Industrial IoT in Engineering and Manufacturing Industries - Benefits and Challenges. In: International Journal of Mechanical and Production, Engineering Research and Development (IJMPERD), ISSN(P): 2249-6890; ISSN(E): 2249-8001, Vol. 9, Issue 2, Apr 2019, 151-160
(2) Yang, H., Kumara, S., Bukkapatnam, S. T. S., & Tsung, F. (2019). The internet of things for smart manufacturing: A review. IISE Transactions, 51(11), 1190–1216. https://doi.org/10.1080/24725854.2018.1555383
Note: This article was updated on the 13th of May 2024
Author
Christian Aadal, Product Manager
