• Category
  • >Business Analytics

What is Manufacturing Analytics? Objectives and Use Cases

  • Ashesh Anand
  • Jul 23, 2022
What is Manufacturing Analytics? Objectives and Use Cases title banner

Currently, a digital transformation is taking place as a result of the introduction of Industry 4.0 and the Industrial Internet of Things (IIoT). The manufacturing sector is starting to leverage analytics powered by real-time production data to enable automation across the business as well as help decision-makers make better, quicker judgments.

 

Massive volumes of data are fed to cloud-based analytics systems by equipment connected by sensors and edge devices, which can analyze and comprehend data more quickly than the human brain. 

 

The organization can then utilize this data to inform immediate decisions and make significant process improvements. Businesses that continuously find new methods to optimize their operations have successful production. 

 

In the past, this required months of in-depth analysis of each process, repeated testing of creative ideas, and finally the implementation of improvements. However, this antiquated way of thinking can ruin manufacturers before they have a chance to improve. 

 

How therefore can manufacturing operations be improved more quickly and effectively? By providing you with more targeted and useful information that help you continuously improve your production line, manufacturing dashboards and analytics can help you optimize your operations.

 

This article will define manufacturing analytics and provide a list of potential applications. Additionally, it will describe the advantages and objectives of manufacturing analytics used in any plant or shop floor.

 

Also Read | What is Lean Manufacturing and How is it Implemented?


 

What is Manufacturing Analytics?

 

The application of machine, operational, and system data to manage and optimize production, including crucial processes like maintenance, quality control, and planning, is known as manufacturing analytics. Manufacturers can decide more effectively and quickly with precise and current data.

 

Manufacturers have long used data to increase productivity and increase their market share. But the way data is gathered now has undergone the most profound transformation.

 

The manual verification and recording of factors, the filling out of forms, and the recording of operation and maintenance histories for the machines on the floor are still common practices in many businesses today. 

 

Unfortunately, due to human error, these methods are very imprecise. They take a lot of time, are subject to bias, and do not produce the kind of analysis needed to make informed decisions.

 

However, with manufacturing undergoing a digital transition, connected devices can reduce the labor required for manual data collecting and documentation. Furthermore, because this software and technologies make use of advanced analytics and algorithms, the conclusions drawn from them are current and much more useful.

 

The next wave of factory analytics is being driven by automated machine data collection, which has unlocked a wide range of sophisticated use cases, from straightforward monitoring and diagnostics to predictive maintenance and process automation.

 

In factory analytics, data capture that records events can be used to improve process efficiency, save costs, increase equipment utilization, and decrease human error—all while providing reliable information on the state of the machines and production patterns.

 

Why do we need Manufacturing Analytics?

 

We are all aware that using all the data produced by end-to-end production lines is necessary at a manufacturing facility in order to maintain production quality, improve performance with high-profit yields, save costs, and optimize supply chains. Exactly for this reason, manufacturing analytics are required.

 

Advanced techniques, including regression and classification, are used in data analytics. The data that is being gathered serves as a source that aids in establishing our objective and makes it obvious to comprehend the cause-and-effect relationship between the information obtained and the advancements made.

 

Utilizing manufacturing analytics, you may easily achieve your goals while saving energy and improving the operating process. You can also use this to discover problems, such as by foreseeing a machine fault that will occur the next week. Saving time and money will help the company remain productive and efficient.

 

Also Read | What is Preventative Maintenance?


 

Objectives of Manufacturing Analytics

 

  1. Manufacturing analytics seeks to move beyond the straightforward collection and display of data (descriptive) to the ability to use that data in real time (predictive) for the detection of issues with equipment and processes, lowering costs and maximizing efficiencies throughout the supply chain with less overhead and risk. 

 

These insights are made available to everyone, from the CEO to the shop floor worker, using manufacturing analytics.

 

  1. An organization's final product can be made better with the use of manufacturing analytics. This is accomplished through a number of procedures, including data-driven product optimization, defect density level management, and trend analysis of consumer input and purchase patterns. 

 

IoT sensors and machine learning models can be used in data-driven product optimization to optimize manufacturing depending on a variety of parameters. 

 

Manufacturers can alter the components that result in increased utilization rates by carefully monitoring product usage. You must maintain a low defect density ratio as a manufacturer. Manufacturers may now more precisely identify process situations that result in higher defect density thanks to data gathered from digital factories. 

 

You may comprehend your consumers' purchasing patterns and lifestyle preferences with the help of customer analytics. Manufacturers can make and supply what customers genuinely want more accurately if they have knowledge of future purchasing trends.

 

  • Additionally, manufacturing analytics can boost throughput and yield. Anomaly detection is one of the key methods it uses to accomplish this. Anomaly detection can notify production managers of flaws in products early on, allowing them to fix problems without slowing down production. 

 

Anomaly detection uses a combination of machine learning algorithms, historical data, and IoT sensors to find out-of-the-ordinary data that could be a sign of an impending issue.

 

  • Analytics for manufacturing can also lower the risks and expenses related to equipment failure or downtime. This is done by locating production lines that are inefficient or bottlenecks, as well as by predicting breakdowns and reducing machine downtime to lower costs using predictive maintenance of important assets.

 


The image depicts different manufacturing analytics use cases such as customer experience management, product design and development, operational cost management, and automation and quality assurance.

Manufacturing Analytics Use Cases


Use Cases of Data Analytics in Manufacturing

 

  1. Recognize your manufacturing chain's supply side

 

Even while purchasing is a basic component of most firms' supply chains, it is one that is simple to overlook when striving to enhance other areas. It might not seem like a big deal to start with a subpar supplier or one that charges a few cents too much per component, but if you're turning out thousands of goods every day, a cent here or there adds up to thousands of dollars on your ledgers.

 

Understanding the cost and efficiency of every component in your production life cycle, starting with the trucks that deliver your suppliers, may be done with the use of manufacturing data analytics. 

 

By showing you how each factor affects the outcome, advanced analytics can assist you in making smarter decisions. Analytics will assist you in identifying any components that are consistently malfunctioning or not performing as they should before they cause a problem.

 

  1. Design systems that are self-healing

 

Manufacturing systems operate under severe pressures all the time, and any interruption in production can result in massive losses. Nevertheless, waiting until a problem arises and then rectifying it is often the greatest option accessible to businesses. The only reason this reactive system has been effective up to this point is because there were no obvious superior options.

 

Businesses can create manufacturing systems that can reliably assess their own need for repairs by combining big data analytics. As a result, systems are more often able to repair themselves and give early warnings in cases where they cannot. 

 

More significantly, data analytics can provide information about which parts malfunction most frequently, allowing you to switch from reactive to proactive solutions.

 

  1. Gain a better understanding of the effectiveness of your machine

 

Time wastage is one of the main issues that manufacturers encounter. Although manufacturing chains can be created with efficiency in mind, various variables may contribute to lowering the line's overall efficiency due to improper installation, misuse, or just a lack of coordination during downtime.

 

Companies can get real-time information into how well their production lines are doing on both a micro and macro scale by merging existing IoT systems with a potent manufacturing predictive analytics

 

Understanding how a single machine's downtime can affect the chain or how alternate configurations might increase overall efficiency should not just be a pipe fantasy. A significant benefit of using analytics in manufacturing is the generation of actionable data that enables you to realize true changes in the overall process.

 

  1. Improve Product Demand Predictions

 

Every producer is aware that they are not only producing goods for the current market, but also for anticipated future demand. Forecasting demand is important since it helps to direct the production process and might mean the difference between successful sales and a warehouse full of unsold inventory. 

 

Forecasts are typically based on historical values from prior years rather than more useful forward-looking information. However, producers may construct a more accurate forecast of future purchase habits by combining existing data with predictive analytics. 

 

These predictive insights, which are based on processes and how effectively lines are functioning rather than merely prior sales, result in more intelligent risk management and less production waste.

 

  1. Improve Your Warehouse Management

 

Storage is another part of the production process that is occasionally disregarded. Products must be stored in warehouses until they are ready to be shipped and then transported to their final location. At this point, seconds and minutes start to matter, especially in a world where "just-enough" and "zero-inventory" models are becoming more and more popular.

 

Finding space for goods to wait is only one aspect of warehouse management. Your bottom line can be improved by implementing the best replenishment practices, efficient arrangement structures, and improved product flow management. Understanding how to manage your warehouses and optimize your inventory is made simpler with advanced analytics.

 

It might be simple to update your manufacturing KPIs and procedures for the twenty-first century. You may develop a more detailed picture of how your manufacturing line runs and how to further streamline it by integrating powerful analytics and visualization tools.

 

  1. Robotization

 

The development of AI and sophisticated machine learning algorithms have almost ensured the rise of robotics. Additionally, as these robots develop, they will provide more data as they carry out their tasks.

 

This data can be integrated into a potent cloud-based manufacturing analytics platform to provide micro-level quality control. The development of robotics will also result in better machine construction from original equipment manufacturers.

 

  1. Warranty Evaluation

 

Warranty service can be a financial burden for many manufacturers. Many times, warranties take a more all-encompassing, "one size fits all" approach. This makes room in the equation for ambiguity and unforeseen issues.

 

Products can be altered or enhanced to reduce failure and consequently expense by utilizing data science and gathering information from field warranties that are currently in effect. It can also result in better-informed product iterations for brand-new product lines to proactively prevent customer complaints.


 

Conclusion

 

Businesses should adapt as the times change. In addition to enhancing production lines, the application of analytics in the manufacturing sector has altered the structure of the business sector and protected it from potential threats. The way has already been prepared for Industry 4.0. 

 

The issue is not whether or not businesses will use analytics. When will they use business intelligence is the question. Because without analytics, the data gathered by intelligent IoT devices is essentially meaningless and there is no way to achieve Industry 4.0. Companies are moving ahead of the competition faster the adoption rate increases. 

 

Despite having one of the greatest rates of BI adoption, the industrial industry still has a long way to go. The largest names in the sector are undoubtedly hopping on the IoT and analytics train, but medium-sized and smaller businesses still need to step up their game. 

 

Companies do not initially need to invest much in analytics thanks to technology like cloud computing and analytics as a service. They only need to try it out to see what great insights and advantages it can yield before expanding on it. 

 

Business users will have the ability to employ self-service analytics to make timely decisions while also being empowered to comprehend their data. Data-driven decisions will undoubtedly be made in the future, and those who are ready to make them will succeed.

Latest Comments

  • Katherine Griffith

    Jul 23, 2022

    Hello everyone, I wish to share my testimonies with the general public about Dr Kachi for helping me to win the LOTTO MAX, i have been playing all types of lottery for the past 9years now. the only big money i have ever win was $3000 ever since things became worse to enduring because i couldn’t been able to win again, i was not happy i need help to win the lottery, until the day i was reading a newspaper online which so many people has talked good things about best lottery cast Dr Kachi who can change your life into riches. So I contacted him and he cast the spell and gave me the hot figures. I played the LOTTO MAX DRAW Behold when I went to check and to my greatest surprise my name came out as one of the winners. I won $60 Millions Dr Kachi, your spell made it wonderful to win the lottery. I can't believe it. Thank you so much sir for dedicating your time to cast the Lottery spell for me. I am eternally grateful for the lottery spell winning Dr Kachi did for me. I’m now out of debts and experiencing the most amazing good life of the lottery after I won a huge amount of money. I am more excited now than I ever have been in my life. In case you also need him to help you win, you can contact: drkachispellcast@gmail.com OR WhatsApp number: +1 (570) 775-3362 Visit his Website, https://drkachispellcast.wixsite.com/my-site

  • Katherine Griffith

    Jul 23, 2022

    Hello everyone, I wish to share my testimonies with the general public about Dr Kachi for helping me to win the LOTTO MAX, i have been playing all types of lottery for the past 9years now. the only big money i have ever win was $3000 ever since things became worse to enduring because i couldn’t been able to win again, i was not happy i need help to win the lottery, until the day i was reading a newspaper online which so many people has talked good things about best lottery cast Dr Kachi who can change your life into riches. So I contacted him and he cast the spell and gave me the hot figures. I played the LOTTO MAX DRAW Behold when I went to check and to my greatest surprise my name came out as one of the winners. I won $60 Millions Dr Kachi, your spell made it wonderful to win the lottery. I can't believe it. Thank you so much sir for dedicating your time to cast the Lottery spell for me. I am eternally grateful for the lottery spell winning Dr Kachi did for me. I’m now out of debts and experiencing the most amazing good life of the lottery after I won a huge amount of money. I am more excited now than I ever have been in my life. In case you also need him to help you win, you can contact: drkachispellcast@gmail.com OR WhatsApp number: +1 (570) 775-3362 Visit his Website, https://drkachispellcast.wixsite.com/my-site