Category: Industry 4.0

A Four-Step Approach

A real-time operational data and analytics pave the way for connectivity, at the top of the smart plant with an estimated 10-20% increase in production and initial cost savings, data analytics is a cornucopia for refinery and mill operations. Additionally, the McKinsey Global Institute forecasted that an aluminium refinery or steel mill may save costs by up to 40% in an accelerated technology adoption scenario that uses data analytics, robots, and other technologies. In this article, it is discussed how a metals firm may profit from real-time data, predominantly in its approaches to asset management and maintenance. Furthermore, to explain the benefits of a real-time predictive maintenance strategy, this article provides an overview of numerous maintenance techniques. Importantly, it also provides a four-step approach that metals industries can use to conduct predictive maintenance and be prepared for Industry 4.0 solution.

1. The development of maintenance:

Reactive, preventive, condition-based, predictive, and prescriptive are the five rudimentary maintenance techniques that businesses may use to maintain plant assets when it comes to asset management.

When there are equipment failures, reactive maintenance must be performed, but this may be an expensive procedure and consequences are increase in downtime that diminishes production. There will still be unexpected downtime and expensive repairs that might have been prevented with an effective approach, whilst preventative maintenance assisting in increased asset reliability. Since 82% of machine failures occur at random periods, even regularly scheduled preventative maintenance is ineffective. Condition-based monitoring is the first step in implementing a proactive maintenance approach. While a machine is operating, data can be acquired by network access to sensors, operator rounds, or other offline methods. By utilizing model-based detection methods, predictive maintenance improves the condition-based technique all the more.

This technique is based on the collection of sensor data online and using data analytics to forecast machine efficiency. Prescriptive maintenance, the highest degree of maintenance, entails the integration of big data, analytics, machine learning, and artificial intelligence. Prescriptive maintenance goes beyond predictive maintenance by automatically applying a solution to an anticipated and a foreseen issue, rather than advising a solution that is subsequently carried out by operators. Prescriptive maintenance, for example, might be used to automatically limiting the speed of an Automated Guided Vehicle for Anode transportation to extend its life. A prescriptive maintenance system is a cognitive system; it has the ability to “think” and can only perform at this level when analytic systems and assets are interoperable. This is the future maintenance system: the idealistic ultimate goal of Industry 4.0.

2.The digital transformation: a four-step plan:

Access to real-time operational data is the most significant aspect of improving plant and asset efficiency. The use of advanced analytics in maintenance allows for the fourth level of maintenance strategy: predictive maintenance, often known as predictive maintenance using Industry 4.0. (or PdM 4.0). This level of maintenance may reduce maintenance planning time by 20-50%, boost equipment uptime by 10-20%, and decrease total maintenance expenses by 5-10%. By following a four-step implementation approach, businesses may begin adopting a predictive maintenance strategy.

STEP 1 Establish an operational data infrastructure:

The first step in implementing a predictive maintenance strategy is to begin using an enterprise operational data infrastructure. For example, OSIsoft’s flagship product, PI System, is a data infrastructure that takes real-time operational data from sensors, manufacturing equipment, and other devices. It then transforms it into rich, real-time insights, linking sensor-based data to systems and people. Setting up a system, such as PI System, to assemble and consolidate operational data is critical in giving insights for subsequent studies. A real-time operational data infrastructure will not only aid increased asset dependability, but will also benefit in improving process productivity, energy and water management, environmental impact, staff health and safety, product quality, and KPIs and reporting. All digital transformation projects rely on real-time operational data. All digital transformation projects, such as deploying a PdM using Industry 4.0 strategy, are built on real-time operational data.

STEP 2 Enhance and contextualize data:

The next stage in predictive maintenance is to ensure that the data is not only gathered or assembled but also adequately upgraded so that it can be converted into a useful information. Contextualizing data is one method to improve it. Sensors, for instance, may gather data indicating that a machine has ceased running. However, such data does not automatically contain the context of events – did the equipment cease functioning owing to the malfunction or because an emergency stop button was pressed? This type of context gives data significance. Context can assist an analyst to determine if a data item is a part of a trend forecasting machine failure or an isolated occurrence. It is critical to understand what data is useful and its relevance to a business or purpose. The OSISoft PI System offers enterprises contextualized data, which allows better operations.

STEP 3 Implement condition-based maintenance:

The third step toward predictive maintenance is to use contextualized data to start with a condition-based maintenance (CBM) strategy. Condition-based maintenance assists in determining the factors that contribute to an ultimate failure and automates maintenance plans and schedules depending on the asset’s present condition. Say, when a bearing’s temperature begins to rise outside of its typical range, it frequently indicates that the bearing may eventually fail. As the temperature rises, the real-time operational data system may notify technicians that this component is nearing failure, allowing them to repair the machine before it completely fails. Basic analytics may be used to improve the real-time CBM offered by the PI System. Identifying a performance trend, such as a rise in bearing temperature of more than 20% in the previous seven days, would allow the algorithm regulating the asset’s maintenance approach to become more predictive. Many of those failure patterns are already known to reliability engineers and are frequently discovered following a breakdown through reliability-centred maintenance analysis. All these well-known patterns may be realised as CBM inside a real-time corporate operational data architecture.

STEP 4 Implement predictive maintenance using Industry 4.0:

The final phase is to implement PdM using Industry 4.0 into action. In conjunction with powerful analytics and pattern recognition technologies, the PI System delivers real-time, actionable data that enables organizations to optimize their operations. When used collectively, these technologies can distinguish patterns that suggest an impending failure. In the previous bearing example, data might be utilized to detect the pattern that causes the bearing temperature to rise over its usual operating range. Once adopted, this method may prominently increase production while decreasing maintenance expenses.

Summary:

Predictive maintenance is the application of advanced and cutting-edge analytics in maintenance. It can give significant and substantial benefits to an aluminium smelter or steel mill. A metals firm, perhaps, may not only forecast equipment failure before it occurs, but can also utilize previous data to trace what happened during an event and mitigate thousands of dollars of damages. Companies must have real-time operational data infrastructure to gather, evaluate, and deploy data analytics in order to implement PdM 4.0. With the PI System, this is possible. With the PI System, businesses may not only make savings but also opens up new income sources, extending equipment life, and increasing production throughput.

• The Digital Revolution: Mining Starts to Reinvent the Future, Deloitte, February 2017
• Beyond the Super cycle: How Technology is Reshaping Resources, McKinsey Global Institute, February 2017
• Improve Asset Uptime with Industrial IoT and Analytics, August 2015
• Predictive Maintenance 4.0: Predict the Unpredictable, PwC, June 2017
• Making Maintenance Smarter: Predictive Maintenance and the Digital Supply Network, Deloitte, May 2017

The fourth industrial revolution is here, and industry 4.0 has greatly influenced different industries. Industry 4.0 utilizes different modern and advanced technologies to establish a robust connection between the digital as well as physical systems. Top cement company Ultra Tech uses this technology & in their first year of operations they saved USD 1 Million, after basing 1755 use case on this platform*.

Industry 4.0 solution has brought opportunities to power up the overall productivity while lowering the environmental impact.
 Cement producers utilise Industry 4.0 solutions and other digital tools, to bring out the efficiencies which are hidden to human eyes by capturing & leveraging the hidden data regarding critical asset performance.
Once these captured data are analysed for a period of time one can apply machine learning solutions to predict the desired output and predict the period of time will this asset will function.

This enables organisational movement from scheduled maintenance model to Predictive maintenance model. This increases the availability of these assets and at the same time cost of maintenance comes down.
One makes some very visible increases in the OEE one of the key cost factors for any organisation.
Industry 4.0- Enabler to greener production processes
The global cement industry, which is very energy-intensive and produces greenhouse gasses, is subject to strict rules as well as environmental constraints. On the other hand, energy consumption has become a primary issue for every cement manufacturer.
 The cement-making process is quite complex, and the electricity and fuel requirements depend on different factors, like the method used to produce cement, quality of the cement, storage of materials, firing lines configurations, raw materials chemical composition, and more.
All these things can complicate energy optimization. However, industry 4.0, which combines IoT, Pi solutions for the cement industry, automation solutions, and more, is opening many new opportunities. Energy optimisation is the area where the data science is used most frequently.

The one biggest compliance issue for a manufacturer is the need for them to become water positive and ensure cleaner operations. The penalties are not only prohibitive but can also result in operation closure which is unthinkable for any investor.
Continuous data monitoring allows real time actionability and complete compliance in this.
Other direct beneficial outcomes of the data integration through creation of data lake having time stamped data capture are:

• Accelerate Growth by Performance Optimization through in-depth process study.
• Applying Industry 4.0 solutions and gaining competitive advantage. Utilising them innovatively to unlock hidden benefits makes sure that one is the most efficient in the industry. As the collected data becomes historic many lessons tumble out to ensure better operational future. Hence longer the term, higher is the competitive advantages. Impact of Industry 4.0 solution on The Global Cement Industry
• Analytic-Driven Predictive Maintenance. With a predictive maintenance solution, cement producers can effectively resolve different maintenance issues well in advance. As a result, they can prevent downtime and unnecessary maintenance effort simply out of a schedule timetable. Besides, helping in boosting operational efficiency and lowering the overall maintenance costs significantly.
• Digital Twin for End-to-End Optimization. Industrial organizations require a new way of operating if they are to address the multiple challenges affecting global markets head on. Geopolitical volatility, Environmental, Social, and Governance (ESG) commitments and disrupted supply chains heighten the pressure for engineers to quickly adapt. Having instant access to a single hub of trusted data enables the right people to make the right decisions when they need to. This is enabled using digital twin technology. A virtual representation of an object or system that spans its lifecycle all the while getting updated using real-time data. One needs expertise in simulation, machine learning and reasoning to make this work. In cement industry the digital twin can enable the cement producers to effectively mirror their production process through a well-designed digital model, and then they can optimize it by using machine learning and artificial intelligence. The digital twins can simulate the cement production process in a dynamic as well as simplified way. As a result, you can create scenarios that can easily change with variables. The best part of the digital twin is that it can suggest optimal and efficient equipment configurations that can help you to increase your output target.

Aveva (technology partner of ecubix) has white paper which puts digital twin benefits as:
Digital twin solutions are transforming engineering projects:
o 3 minutes or less to find actionable asset information
o 2 months to deploy across the full business unit with a cloud solution
o 10% increased staff productivity
o 30% or more reduction in unplanned downtime

Source-https://engage.aveva.com/rs/986-YIS-805/images/Whitepaper_AVEVA_AIM_EmbracingDigitalTwinTech_22-07.pdf

Trusted engineering data is at the core of every successful digital twin. Engineering data provides the structure from which the twin can be created and allows 3D visualization. Using predictive quality models, cement producers can forecast cement quality with near to 100 percent accuracy in real-time.
Ecubix creates digital twins through linking the machines through innovatively using technologies like the internet of things, embedded data analytics, machine-learning algorithms, & Pi solution for the cement industry.

• An Optimization of Supply Chain and Logistic- With the IoT for the cement industry, you can create a Smart Cement Factory that can offer you real-time supply chain information by effectively tracking products, equipment, materials, and more while they are moving through your supply chain.

 So, what are you thinking now? If you want to improve the production capacity while keeping your production cost and carbon footprint low, then it’s time to employ Industry 4.0. Besides, there will be greater visibility of every aspect of your business.

Once you are a part of any manufacturing industry, Industry 4.0 will be a general point of discussion.

This is an age of competition and an issue of being first amongst equals. Once your competitor starts drawing advantages from applying Industry 4.0 solutions, you need to get it as well. In long run It may be a question of one’s survival. Present manufacturing technologies are evolving to fully encompass both automation information and data exchange. They are integrating all existing systems through using cloud computing with cyber-physical systems, augmented reality, and the Industrial Internet of Things (IIoT). In short, one’s journey to future does not even begin without applying Industry 4.0 solutions.

Benefits of using Industry 4.0

A. Increase of productivity- As already explained the three components of productivity get instantly affected positively through application of Industry 4.0 solution. Machine availability the biggest challenge is first benefit by ensuring better maintenance schedule and pre-empting breakdowns. The clear visibility in RM supply chain and quality output gives a much larger control over this one most important factor.
B. Remaining competitive- Proper management of efficiency in production and optimization of supply chain can help an organization to fulfill the orders of the customers in different market segments. On top of this effective distribution strategies helps an organization to remain competitive in highly competitive manufacturing industries.
C. Increased Knowledge sharing & collaborative working- Industry 4.0 comprises cloud-based information to share technologies that help sharing relevant information within different departments so that good practices by one can be shared across the organization virtually seamlessly. Also, it ensures dismantling of departmental silos so common in large organizations. Team collaboration which results makes it easier for the organization to achieve the organizational targets.
D. Cost effectiveness- The ability provided by Industry 4.0 platform is performing repetitive tasks without any error. The chances of human errors also remain less in this process. On the other hand, it also becomes possible for the organizations to re-organize their workers as per task complexity rather than task repeatability. As a result, the labor cost of the company per unit of production reduces significantly.
E. Flexibility & agility- Scaling of production up and down or to include new products lines becomes much easier. One has to only provide crisp SOPs for the changed process. Hence Industry 4.0 opens opportunities for one-off manufacturing systems and high-mix manufacturing systems.
F. Better customer experience- Quality enhancement and near instant root cause analysis ensures reduction of human errors in manufacturing. The overall control on each aspect of production and finished goods handling helps enhance the customer satisfaction. to manage the availability of the products in different markets so that the customers do not face issues in availing those products.

Challenges of using Industry 4.0

A. Cyber Security Issues- The use of IoT-based technologies and cloud- based technologies can lead to cyber security issues. Cyber-attacks performed on the servers and databases of the companies might lead to issues like data losses and data manipulation. Ecubix provides a highly protected platform and if demanded we can provide a security which is the highest possible in the industry. Through this we can assure no possibility of data theft or any kind of manipulation.
B. Technical issues- Improper maintenance of these technologies or inefficient handling of the machines can lead to technical issues. Such technical issues can also create inconveniences in managing operations. Ecubix provides a complete AMC of the systems it provides. Hardware to software. We are end-to-end service provider. This makes us the best possible maintainer of our systems.
C. Increase of technology maintenance cost- Any form of technology once applied is liable to get redundant as well as rendered useless as organization grows. However, the platform provided by ecubix is scalable to a virtually infinite level. Our customers have been with us since the time we have implemented solutions there.
D. Challenges related to employee training- After implementing industry 4.0, it is very important for the manufacturing organizations to train their employees properly for using digital technologies and smart machines in the production activities. Without proper training, they cannot handle those technologies properly and, it would lead to technical issues. Ecubix provides a continuous training through premade schedules as per the experience an organization gains though the industry 4.0 usage.

The concept of Industry 4.0- was coined to describe the phenomenon for merging of real and virtual worlds based on Cyber Physical Production Systems (CPPS).

It was evolved way back in 1960-70 aimed at enhancement of productivity of manufacturing organizations. Today Industry 4.0 is the current trend of automation technologies used for creating a smart factory. The figure below shows few components of Industry 4.0. Through these technologies we integrate different departments of the manufacturing companies to streamline their manufacturing operations.

Applications of Industry 4.0 in the manufacturing sector as implemented by ecubix. Ecubix inducts Industry 4.0 solution platform which provides:

A. Real-time information regarding the whole manufacturing process. The visibility thus created throughout the value chain allows optimization in:

• Raw material used in production,
• Logistics in the supply of the materials through different stages
• Origin of the material and it’s quality parameters
• Different activities associated with the production like improving production rate. Or in total quality management. Directly impacting OEE of the organization.
  Thus, distribution of resources and goods can be controlled effectively to manage the production activities effectively.

B. Next is bringing the risks of surplus production and the wastage of resources for surplus production in front. Implementation of Industry 4.0 is very much important for managing an end-to-end digital supply chain.
C. Provide data to organization in a contextualized form. This enhances the usage of data it’s understanding leading to improvement in the productivity of the workers.
D. Next is validity of the data. Generally, when data is used to create predictive models or applying AI to them 80% of the data analyst team gets used up in data massaging. The platform provided by ecubix provides a pre-validated data which makes it ripe to be instantly fed to AI tools.
E. Once validated data is available, we need to analyze the data using various statistical formulae. The platform has pre-embedded formulae or algorithms in it. What more it allows additional analytical tools to be embedded in it. Thus, it enables the stake holders specializing in their area of expertise to play with the data and freely come out with numerous efficiencies creating use cases. Our platform is completely free from coding needs.
F. Last but the most important part of any data integrating platform is its ability to provide visualization of such a nature that it enables the users to get a constant stream of decision enabling visual form which provides a near instant root cause analysis and an ability to simplify the processes in a manner where the operating team is able to take corrective action before any issue creates a loss making preposition.

Adoption of Industry 4.0 and IoT-based automation technology in the manufacturing sector Though many of large manufacturing organizations have shown interest to implement Industry 4.0. But after the pandemic the need of this has become a key reason for their success. Estimate shows by 2024 the organizations opting for the solution is expected to grow by 70%.

However, SMEs face different types of challenges in the implementation of Industry 4.0. The common issues being lack of talent and technical skills and the lack of resources and funds for implementing those automation technologies. However, ecubix has such unique process of implementing the solution that instantly within a period of three to four months organizations are able to realize cost savings to the tune that returns of their investment happens very fast. Before implementation the pilot evolves the system in such a manner that it is the operator level who grab the learnings first.