Data Analytics in the Manufacturing Industry
Find out how you can implement manufacturing analytics into your business. From product quality to supply chain, learn how you can benefit from smart manufacturing solutions and how manufacturing industry has shifted with new technologies.
According to Research Dive, “the global smart manufacturing market will be surpassing $303.0 billion by 2026, at 6.4% CAGR from $171.5 billion in 2018″. More and more manufacturers converge their operations with new technologies such as Artificial Intelligence and machine learning which are truly shifting the manufacturing industry into a new era. A vital piece of this process is data capturing and data analytics which will lead to optimisation of the supply chain, accelerated product scheduling, reduced costs, increased profit and gathered forecasts created by AI and IoT technology.
What is it All About? Collecting, Processing, and Analysing Data
Data analytics is transforming all kinds of industries, including manufacturing. But what is data analytics in the context of the manufacturing industry? As a big part of Industry 4.0, manufacturing analytics refers to the use of predictive analytics, big (machine) data, and the IoT to improve the operational functions of a manufacturing company. It is used to enhance productivity, ensure product quality, reduce costs, and optimis supply chains while providing end-to-end visibility across the plant floor. It is a cloud-based analytics software where the sensors collect data from machines, operations, and systems to provide you with real-time insights with IoT technology. With the real-time and manipulated data and insights, you get to take action in the fastest way possible or enable your business to respond automatically in real-time.
The unlimited data your software can gather identifies the areas for improvement and allows you to enhance your decision-making process while accelerating it and reducing human error. It captures the data from machines to people, throughout the whole process of your factory. You, as the manufacturer, can use this big data to produce more reliable and faster machines or to increase automation in your enterprise.
Where Does This Apply in Your Business?
You may ask, “But where does this apply in my business? And how can I benefit from it?” Well, the main business cases of manufacturing analytics include supply chain operations, product quality, field service & support, and creating an efficient factory, which are the main operating units of your manufacturing business.
Supply Chain
Supply chain operations are becoming more complex and time-consuming and reacting to supply chain disruptions and identifying risks in logistics in real time are now vital necessities for manufacturers. Data analytics plays a huge role in automating these tasks for you. It enables you to track, analyse, and streamline the whole supply chain process. Data analytics also provide you with forecasts of customer demand and future trends, enable automated order management, create better inventory optimization, and increase supplier performance with transportation analytics. These lead to a rise in customer satisfaction and overall increased efficiency throughout the organisation.
One of the users of this technology is the Coca-Cola Company: according to Fortune Business Insights, it was able to save around USD 45 million annually with big data analysis for vehicle routing systems. Another example is John Deere, who used data analytics in inventory control and saved USD 900 million over two years.
Product Quality
With real-time remote monitoring, the quality of your product increases with the transparency provided in the production field. One of the targets of manufacturers is to keep defect density levels low in the factory. The collected data would provide the manufacturers the information on which processes or steps lead to defects and thus enable them to manage defect density levels. The data can also detect which part of the product is used most and least, and manage the production of those components accordingly, which will lead to a higher rate of usage.
Bring Light to The Dark Side
With greater visibility comes better alignment. With greater visibility comes better management. Manufacturing analytics can help you align with your business’s key metrics and goals. When a constant stream of data coming from your factory is collected, manipulated, and analysed by software combined with AI and the IoT, it provides agility and efficiency. As manufacturing analytics comes with great benefits, not employing it causes a great amount of manual work, undetermined bottlenecks, increased costs, and missed potential. As the usage of data analytics provides light and visibility, not employing it brings darkness to your manufacturing processes. The problems manufacturing analytics will help you to solve include scheduling issues, accounting for labour hours and production times, and minimising the gap between what you think is happening on the shop floor and what actually happened.
As a final point, with analytics, you will measure and improve the performance of your company. You will be able to enhance quality assessment processes, increase operational efficiency by maximising yield and throughput, increase reporting quality, and streamline warehouse operations. You will be able to reduce costs associated with equipment downtime and predict maintenance with remote monitoring before it affects your production. The goal is to meet the performance and quality metrics in the most automated way possible and you will achieve this with data analytics.
Talent and Data
“How can I implement this in my factory?” might be one of the questions in your mind right now. Besides searching for the key industry players or directly investing in smart manufacturing solutions, we believe companies must know their digital maturity levels to know where they are now, and their future goals to capture the most value from these solutions. Companies that want to join this digital transformation journey need enablers such as technology, talent, and data, and need to know their levels in these dimensions.
Companies should first be prepared for the culture change to adopt a data-driven operational focus. Since digital projects require the right skills and new capabilities, companies need to involve domain-level experts working in supply chain management, process technology, and technology specialists or domain experts working in areas such as software development, data science, and automation. Also, companies need to encourage skill development in-house in these areas.
Let’s Measure Your Success Together
Digital transformation must be the number one priority for manufacturers striving to remain profitable as hard-to-control and profound changes emerge in the manufacturing and supply chain world. At Digitopia, we understand how to improve productivity for the advanced manufacturing process.
With Digitopia, find out how to follow these emerging trends in the manufacturing industry and converge with Industry 4.0 to gain a competitive advantage. We aim to measure your success in this area and direct you to achieve operational excellence in your digital transformation journey.
