Data Analytics in Digital Manufacturing: How Big Data Transforms Manufacturing Industry

Data analytics converts raw data into actionable insights. It includes various tools, technologies, and processes to find trends and solve problems using data. Data analytics can shape business processes, improve decision-making, and foster business growth. Data analytics helps companies gain more visibility and a deeper understanding of their processes and services. It gives them detailed insights into the customer experience and customer problems.

According to Amazon Web Service (AWS), big data analytics follows five steps to analyze large datasets: data collection, storage, processing, cleaning, and analysis. Data analysis is the step where raw data is converted to actionable insights, and there are four types of data analytics. Descriptive analytics is understanding what happened or is happening in the data environment. It is characterized by data visualization such as pie charts, bar charts, line graphs, tables, or generated narratives. Diagnostic analytics is a deep-dive or detailed data analytics process to understand why something happened. It is characterized by techniques such as drill-down, data discovery, data mining, and correlations.

Predictive analytics uses historical data to make accurate forecasts about future trends. It is characterized by machine learning, forecasting, pattern matching, and predictive modeling techniques. In each technique, computers are trained to reverse engineering causality connections in the data. Prescriptive analytics takes predictive data to the next level. It predicts what is likely to happen and suggests an optimum response to that outcome. It can analyze the potential implications of different choices and recommend the best action. It is characterized by graph analysis, simulation, complex event processing, neural networks, and recommendation engines.

Predictive maintenance or maintenance analytics is one of the predictive analytics cases. Predictive maintenance is a condition-based maintenance strategy only concerned with maintaining equipment that is actually due for maintenance, whereas preventive maintenance is a scheduled-based approach where equipment is maintained at regular intervals regardless of its condition. This creates a lot of waste, as parts that could have continued to function longer are needlessly replaced or repaired.

In contrast to preventive maintenance, reactive or corrective maintenance is when repairs are only done once a problem occurs. This may seem like the most obvious solution., but it can actually be quite costly and disruptive. Note that when a problem is detected, it may be too late to avoid unplanned downtime. Predictive maintenance has the benefits of both worlds without any downsides. Using data and analytics allows us to perform maintenance when needed, avoiding the waste associated with preventive maintenance and the unplanned downtime associated with reactive maintenance.

According to Research Nester, the global predictive maintenance market is estimated to garner a revenue of USD 81,582.5 million by the end of 2031 by growing at a CAGR of 31.9% over 2022 – 2031. Further, the market generated a revenue of USD 5,261.4 million in 2021. The market’s growth can be attributed to the growing need to reduce downtime and maintenance costs. Predictive maintenance predicts the best time for equipment maintenance, which also makes the maintenance procedure cost-effective, reducing the wastage of time and resources on the occasion of machine breakdown. Large factories lose 323 productivity hours annually on average. The average cost of lost sales, fines, downtime for employees, and restarting production lines is USD 532,000 per hour or USD 172 million per facility yearly.

The Asia Pacific predictive maintenance market, amongst all the other regions, is projected to hold the largest market revenue of USD 23,985.2 million by the end of 2031. The region’s market will grow at the highest CAGR of 35.4% over the forecast period. The market in Asia Pacific garnered a revenue of USD 1,183.8 million in 2021. The market’s growth can be attributed majorly to the rapid penetration of digitization in the company. Around 70% of major corporations and middle-market businesses in the APAC region have a digital transformation strategy in place, with Taiwan leading the pack.

Article by: Asst. Prof. Suwan Juntiwasarakij, Ph.D., Senior Editor & MEGA Tech