Global
What is Industry 4.0
The fourth industrial revolution, or Industry 4.0, as it is popularly known, was coined in 2011 to signify the future of manufacturing. It is meant to evolve the industry based on the advances bought about by the previous three industrial revolutions. While computers and automation spearheaded the third industrial revolution, Industry 4.0 is driven by the Industrial Internet of Things (IIoT). IIoT can be visualized as a huge network of physical assets fixed with sensors that can connect and exchange data with devices and systems through the internet. Through data exchange, these sensors can detect and respond to changes in the industrial asset, be it light, temperature, motion, pressure, etc. They can warn of potential issues before they become bigger challenges.
What is digital industrial transformation
Digital industrial transformation effectively uses digital technologies to transform industrial processes and move towards Industry 4.0. It is about enhancing manufacturing efficiency and strengthening the business’s growth curve. With the effective fusion of technologies such as cloud computing, IoT, AI-ML, edge computing, and digital twins, it is also cost-efficient, saves time, and reduces errors due to manual intervention. Here are a few characteristics which are indispensable and promising.
- Effective data leverage: It’s more machine-dependent and less human. With physical systems connected with sensors that are integrated into a network, most decisions are automated based on performance data. The data is collected in a data lake & AI-ML models are used to derive insights from this data to enable autonomous decisions, reducing the need for centralized controls and operator interventions.
- Improves operations: Using data, factory staff can make faster decisions and understand equipment availability, performance outcomes, quality, and productivity. They will be able to proactively understand the cause of faults and maintenance requirements and take suitable corrective measures. Through data interoperability, enabled by IoT, companies will be able to share information with their suppliers, vendors, and partners more seamlessly.
- Virtual Instances: Virtual instances of physical assets, systems, and processes can be created. These virtual instances help in monitoring & optimizing production process. It’s a secure virtual replica of the factory. This has many uses such as simulations, running software tests, and testing configurations. It is an ideal way to understand the outcomes without impacting the production on the factory floor. The most common kind of virtual instances are Digital Twins.
- Adaptive production: Enables flexible production systems that adapt to changing market demands, product customization needs, and efficiency requirements. By dividing production lines into smaller modules, that can be added, removed, or reconfigured based on production needs without impacting the assembly line.
How Digital Transformation Technology is changing the Industry
With its characteristics of flexibility, automation, and modularity, the digitalization of industry can widely impact the manufacturing organization. Here are a few value drivers which can help manufacturing companies identify opportunities to optimize their production process.
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Asset optimization: Maximizing machine production time is critical. Capabilities such as predictive maintenance can reduce machine downtime and increase machine life. Digital twins and predictive maintenance offer insights into the performance of physical objects and systems, enabling businesses to foresee any maintenance and repair schedules in advance. This reduces machine costs and increases machine availability.
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Labor productivity: Improves the operating speed of workers by reducing stress in executing complex tasks. Cobots (collaborative and sensitive robots) can be used to work with workers on the floor to ease their workload. They can take up hard, repetitive tasks, as the space required to operate is extremely low. They can share the same workspace without fencing as these cobots are very safe. They are precise and flexible, capable of delivering high-quality products, and versatile in handling tasks from testing to material handling.
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Inventory management: Real-time inventory tracking ensures more accurate inventory level estimates for better purchase, production, and shipping decisions. With the help of AI-ML driven predictive analytics, companies can forecast demand, reducing risks of stockouts or overstocks. Automating tasks such as order fulfillment and stock replenishment can speed up moving the products from the warehouse to the customer.
- Quality: Product quality can be controlled using statistical process controls (SPC) and advanced process controls (APC). SPC involves using statistical methods to monitor and control manufacturing processes with the help of real-time data and analytics. APC uses mathematical models and real-time data to optimize processes, identify quality issues and meet changes in quality demands.
It is a definite win for early adopters of Industry 4.0 as they are more mature to handle crises and competition. However, most firms are still reluctant to embrace modern manufacturing practices. The risk of not investing is huge. They might lose market share to more agile competitors bringing in more technologies such as IoT, analytics, and robotics. Customers get max bang for their buck as they can meet their custom needs and quality standards, all at a reduced cost. Manufacturers must sense the urgency of adopting Industry 4.0 and its technologies by realizing its impact throughout the production processes, including supply chains.
Challenges and Benefits of Industrial Digital Transformation
Let us look at challenges of implementing industrial digital transformation. One big roadblock is that to deal with legacy infrastructure, which can be a real pain. Most factories are still happy with old technology which is not interoperable with digital technologies. Employees might show resistance to adopt new technologies and the change it brings with it. Cybersecurity is another pain which must be dealt with, due to the increase in the volume of data. Cost is another factor as most digital solutions are expensive. Meeting legal and compliance standards can be a challenge as it can spike the transformation costs.
Now, here are the benefits. As we have seen, automation, optimization, and connectivity form the core of industrial digitalization. it empowers stakeholders to evaluate concepts before they are built, optimize output across production lines, and even run real-time simulations of a real factory to reduce downtime time and cost. The following technologies can significantly impact in the digitization of manufacturing operations and processes.
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Internet of things: A network of physical assets with sensors connected over the internet that collects and shares data; this data can be used to extract insights to improve operations
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Cloud computing: The key to the success of industry 4.0 as it helps to meet the scaling demands of integrating and connecting production, distribution, supply chain, and engineering departments.
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Artificial Intelligence & Machine Learning: AI & ML algorithms can be used to sift through the data generated by IoT sensors and create insights to optimize operations.
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Edge computing: By analyzing data at its source reduces the time lag for a response. This is needed as some issues need to be dealt with immediately. It isn’t practical to send the data to the cloud and get it back after analysis, as this can be time-consuming. Edge computing ensures data analysis is done at the source.
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Big Data: Big data analytics can be used to consolidate data from production plants. The data can analyze and uncover hidden logjams in production, keep production efficiencies intact, and mitigate breakdowns and machine downtime risks.
- Cyber security: Digitization can expand the attack surface. A digital smart factory combines virtual and physical systems with unique vulnerabilities, making them susceptible to cyber-attacks. A risk-based approach is a must to ensure vigilance across the manufacturing ecosystem and reduce threat risks.
The need for an industrial digital transformation service provider
Industry 4.0 answers the need of manufacturing companies facing increasing market demands and customer needs to deliver sustainable, personalized products and services. To remain relevant and competitive, they need the help of digital transformation consulting firms, or top digital transformation companies who can help them leverage the power of data, IoT, AI/ML, and next-generation digital transformation technologies to enable automated operations. Ness has proven itself a digital transformation company in USA who can help firms design the end-to-end roadmap, reinvent operating models, data governance framework, performance management, and security to accelerate the transformation. We can help with company digital transformation, improve their equipment effectiveness using digital twins and digital intelligence, lower production cost, improve safety and ensure quality outcomes. Ness also has a good ecosystem of technology providers who can help scale faster and accelerate the migration from a legacy manufacturing model to a more modern and digitized industrial framework.
