….Implementing an Internet of Things solution (commonly referred to as IoT) can provide your business with extensive data analysis and a comprehensive look into your products and production process.
The manufacturing industry is constantly being pushed to make its processes more efficient while reducing overall costs. So what makes IoT solutions viable for manufacturing companies to accomplish these goals?
Smart factories!
What Is a Smart Factory?
The idea of a smart factory is to utilize various modern technologies in diverse combinations to establish a flexible, accommodating manufacturing capability. It uses technologies such as the IoT, artificial intelligence, machine learning, and robotics to improve the efficiency, quality, and flexibility of the manufacturing floor production process.
In a smart factory, machines, equipment, location-tracking sensors, and systems are interconnected so that data can be collected and analyzed in real time. Real-time data collection and analysis in traditional factories enables intelligent decision-making and predictive maintenance. Smart factories will usually have a custom manufacturing mrp software.
Smart factories are also designed to be highly adaptable and can quickly adjust to changes in demand, product design, or smart manufacturing processes. The goal of smart factory initiatives is to increase manufacturing productivity, reduce costs, and optimize resource utilization while improving product quality and customer satisfaction.
What Is IIoT? Why Do Businesses Procrastinate Implementing It?
The Industrial Internet of Things (IIoT) is taking the framework of IoT and applying it in an industrial setting. IIoT enables users securing industrial systems to connect machines, sensors, and devices used in the manufacturing process across various sites and monitor their equipment with an equipment management system.
Businesses in the manufacturing industry can have many concerns about implementing an IIoT solution for their manufacturing needs. The most common concerns are high implementation costs, lack of internal expertise, and the possibility of disrupting existing processes and systems.
Delaying the adoption of IIoT can mean your business misses opportunities to improve supply chain efficiency, reduce costs, and enhance customer satisfaction. Here are more common concerns and how implementing an IIoT solution may still be the right solution for you.
IIoT Will Eliminate Demand for Personnel
While IIoT has the potential to automate some tasks previously performed by humans, like any machine learning solution, it is not intended to replace them. Instead, the goal of IIoT is to augment what workers today are capable of.
Concerns about automated solutions eliminating people’s jobs are understandable. The increased efficiency and productivity enabled by an IIoT can lead to the growth of businesses and even the creation of new positions!
Embracing IIoT and other automated technologies can make businesses more competitive in the manufacturing industry and better positioned to meet the demands of an increasingly complex and interconnected world.
IIoT Requires Total Readiness
While implementing an IIoT solution requires preparation and planning, total readiness isn’t necessary.
Businesses should start small by identifying the areas where IIoT can have the greatest impact on their manufacturing operations. A great first step is conducting pilot projects and proof-of-concept tests. This approach quickly identifies unique challenges faced by that particular manufacturer while generating some quick wins.
Experienced IIoT solution providers can help businesses navigate the complexities of implementing the technology, ensure data security and privacy, and identify the right technology solutions. By starting small and working with experienced partners, businesses can build momentum and develop a roadmap for scaling their IIoT initiatives over time.
Upgrading is Not Cost-Effective
Implementing an IIoT solution in a factory will require an upfront investment, but the long-term benefits and return on investment ultimately make it cost-effective.
IIoT solutions can help businesses reduce costs, increase operational efficiency, improve product quality, and grow revenue. A phased approach to implementation, like the pilot projects and proof-of-concept tests mentioned above, can help minimize upfront costs and risks.
Cost-benefit analysis can help businesses make informed decisions about IIoT investments and ensure they are cost-effective in the long term.
Leverage Smart Manufacturing Technologies to Stay Ahead: IIoT Benefits to Embrace
To leverage smart manufacturing technologies and stay ahead with IIoT benefits, businesses should start small by implementing pilot projects and partnering with experienced IIoT solution providers. They should invest in employee training and develop a roadmap for scaling IIoT initiatives over time. Continuous monitoring and evaluation of IIoT solutions are important to ensure they are delivering expected benefits and remain competitive in the evolving manufacturing sector.
Real-time Monitoring and Asset Management
In a typical manufacturing environment, vendors don’t know the customers when a product sells, and they won’t be informed if their product doesn’t work until customers take action. IoT solutions allow manufacturers to collect and analyze data from a product after its deployment and integrate changes into new releases. Aside from building customer trust, they may provide timely and knowledgeable client assistance if production equipment breaks down.
Streamlined Business Operations
Using an IIoT solution can include using innovative technology to track and retrieve items from storage and other facilities. The latest product lines may have been virtually evaluated in digital twin machines rather than first-time production failure. IoT sensors monitor transport conditions to minimize damage and avoid delays in the production line. They are also used to place new deliveries to ensure that there is enough inventory to fulfill the orders. IoT can improve manufacturing by helping customers increase efficiency.
Asset Downtime Prevention with Predictive Maintenance
Several companies have lost hours from equipment failures. In a large-scale industrial manufacturing plant, the total cost of an equipment breakdown can set even the most well-established companies back.
With the use of IoT technology, companies can perform predictive maintenance to detect malfunctioning equipment early in production, thereby decreasing downtime. IoT sensor installations for industrial machines can collect performance-specific information, like pressure, vibrations, etc., in real-time without equipment downtime.
Enhanced Labor Management with Smart Robotics
Businesses can leverage smart robotics using IIoT to enhance labor management, improve safety, and increase productivity. It is important for industrial companies to remain proactive and embrace change to remain competitive in the evolving manufacturing landscape. First, identify the areas where smart robotics can have the greatest impact on manufacturing sector labor management, such as reducing manual labor, improving safety, or increasing productivity.
Invest in training and education to ensure employees have the skills and knowledge needed to work with smart robotics and adapt to the changing manufacturing landscape. Then, develop a roadmap for integrating smart robotics into labor management processes over time based on the results of pilot projects and feedback from stakeholders. From there, you can continuously monitor and evaluate the performance of a smart robotics solution to ensure they are delivering the expected benefits and adjust strategies as needed.
Digital Twins
A simple way to apply an IIoT solution to your manufacturing processes is to create a digital twin of your manufacturing facilities. By creating detailed digital copies, you can run simulations of processes and discover any issues or hiccups without risking any damage to physical machinery or wasting materials and time.
The digital twin can be used to simulate different scenarios and make adjustments in real time, reducing the time required to bring new products to market. Overall, creating a digital twin of a manufacturing process can help businesses can reduce waste, improve resource utilization, and ultimately reduce operating costs.
Smart Levels: Four Levels of a Smart Factory
There are four levels to a smart factory:
- Level 1: The sensor level, where IoT sensors gather data from machines and equipment on the factory floor.
- Level 2: The network level, where data from the sensors is transmitted and aggregated to a central system.
- Level 3: The control level, where the data is analyzed and used to make decisions in real-time to optimize the manufacturing process.
- Level 4: The enterprise level, where the data is integrated into business processes, supply chain management, and other strategic decision-making.
These levels of operational technology are interconnected and build on each other to create a fully integrated smart factory. By leveraging technologies such as the Industrial IoT (IIoT) and artificial intelligence, businesses can create a hyperflexible, self-adapting manufacturing capability through a digital transformation that can help them stay competitive in the rapidly evolving manufacturing landscape.
Level One: Available Data
This level is where physical sensors and other IoT devices are located on the factory floor to collect data from machines and equipment. This data is typically related to machine performance, productivity, and quality, among other things. Examples of IoT sensors used in diverse industrial data at this level include temperature sensors, pressure sensors, and motion sensors.
Level Two: Accessible Data
This level involves the transmission and aggregation of data from the sensors and other IoT devices used in Level 1 to a central system. This is typically done using wireless or wired communication technologies, such as Wi-Fi, Ethernet, or Bluetooth. The data generated is typically stored in a centralized database or cloud-based platform, where it can be accessed and analyzed.
Level Three: Active Data
This level involves the analysis of data collected from Levels 1 and 2 and using it to make decisions in real time to optimize the manufacturing process. This level typically involves the use of advanced analytics and machine learning algorithms to predict machine failures, optimize machine performance, and improve overall production efficiency. At this level, machine control systems are implemented to enable automation and autonomous decision-making.
Level Four: Action-oriented Data
This level involves integrating diverse industrial data collected from Levels 1-3 into business processes, supply chain management, discrete smart manufacturing, and other strategic decision-making processes. At this level, the data is used to make strategic decisions related to product development, marketing, value chain, and other key business areas.
Making the Factory of the Future Real—Today
IoT application development can help you create new business models, deliver improved customer experiences, and generate more revenue streams. Adopt new technologies such as cloud computing, artificial intelligence, and big data analytics to optimize production, improve connected supply chain operations, and reduce costs.
Identifying areas of improvement and implementing changes to optimize performance over time ensures that you’re focusing on continuous improvement for your processes. IIoT application development is just one piece of the puzzle, and by combining it with other strategies, businesses can unlock their full potential and stay competitive in the rapidly evolving smart manufacturing landscape.
Ready to dive on in? Reach out to Geneca to talk to an experienced professional today!