How technology & big data will make tomorrow’s manufacturing decisions different from today’s

Posted on 14 Sep 2017 by The Manufacturer

Understanding data is increasingly important for manufacturers with the advent of big data. Data has been described as the 'new oil' for businesses, so what is the best way to make the most of your data?

FICO have recognised that Industry 4.0 is the current phase in the digitalisation of the manufacturing sector. Key disruptors have been the rise in data volumes (big data), computational power and connectivity (IoT, sensors) and the application of advanced analytics (predictive / prescriptive), artificial intelligence and big data Manufacturing_Image_1 photo courtesy of FICOmachine learning capabilities.

These have facilitated an increase in the amount of data collected from production machines and processing it in real time to produce better information leading to improved decision making and increased productivity. This approach is changing the very way people and business make decisions.

Big data only becomes useful when it enables us to make better decisions, so it’s imperative that decision-makers have what they need to understand the data they rely on. One of the tools that helps extract value from big data is machine learning—algorithms and processes that enable complex analysis to evolve and improve as new scenarios are added.

Machine learning approaches data analytics in much the same way as the cortex of the human brain does, so that analytics such as neural network models can continuously learn and adapt to new data.

Not all analytics for decision-making are created equal. Different types of analytics can be useful for specific aspects of decision-making. And the more complex the decision—with more variables involved—the more analytics types you’ll need to engage in your process.

As complexity increases, analytics grows more valuable

 Value and Difficulty Graph - Photo Courtesy of FICO









Predictive & Prescriptive analytics and the power of IoT is preventing costly production failures

With regard to predictive maintenance, FICO has seen organisations identifying this as a strategic area of focus to help get better productivity & efficiencies. Companies are leveraging advanced analytic software capabilities to better analyse sensor data and report potential failures in real time.

Manufacturing_Image_2 Photo courtesy of FICOUnexpected failure or performance degradation of production equipment can significantly impact productivity, product quality and maintenance costs within any manufacturing organisation. It’s also difficult to get operations ‘back on track’ after these failures occur.

The good news is that, via the IoT, intelligent use of sensor data, machine learning and optimization capabilities can help companies take a proactive approach to predicting failures and re-optimizing processes around them.

FICO are seeing the rise of low cost and increasingly sophisticated and sensor technology in manufacturing plants – and they are the building blocks of Industry 4.0. Organisations with the most expensive manufacturing equipment are usually the first to move on sensor data ensuring they get as much value from their machines as possible.

The challenge for many is that they cannot actually aggregate the sensor data into a database or the volume of data itself simply paralyses their ability to find meaning, while others are still tracking production manually. Leveraging the right data processing and analytics software and expertise (both predictive and prescriptive) is vital to unlock business value and improved productivity.

FICO has more than 60 years’ experience in pioneering innovation and delivering advanced analytics and decision management solutions across multiple industry sectors. Our solutions have been widely deployed in many large, global, complex organisations and have delivered real business value, improved operational efficiencies and enhanced overall business performance.