Is Industry 4.0 really the manufacturing savior it claims to be?
Manufacturers are under pressure. They need to do more with less which often means finding ways they can save money and expand margins. The options? Making more finished products and selling those products cheaper; having less costly downtime and less waste; and having fewer defects and higher satisfaction, all while requiring fewer raw materials, resources and energy. Sounds like a lot? It is. History is littered with examples of manufacturers failing to balance these sometimes conflicting priorities. Will Industry 4.0 be the much-anticipated savior?
Industry 4.0 is the next wave of change
Many manufacturing leaders – from business or plant management down to operators – have seen waves of change before. In the 1980s the focus was about lean and lean principles. In the 1990s the conversation shifted to outsourcing with production moving to low-cost countries offshore. Most recently in the early 2000s some of this production has brought back with automation leading to additional efficiency. Yet after each wave – lean, outsourcing, and automation – the demands from the business have increased again.
The latest wave is Industry 4.0. Like its predecessors, Industry 4.0 holds lots of promises around smarter supply chains, manufacturing processes disruption, and even end-to-end ecosystem transformation. But there are also questions about how the theory and hype square with existing investments, established processes, and near-term demands.
Industry 4.0 is viewed as the savior — but is it really?
Industry 4.0 is about connectivity and data integration driving smarter factories and supply chains. It is based on IoT principles that allow firms to bring in new data about the manufacturing process. With inexpensive sensors and connectivity technologies, manufacturers can integrate dozens of new production variables. What was the humidity on the factory floor? What was the vibration of the manufacturing equipment? What was the temperature of that machine?
Traditionally this data has not been factored into the manufacturing process. It was collected but not integrated or not collected at all. This is changing. Firms can now pull new information into data models and understand the correlation of variables to factors like equipment downtime, quality, and resource utilization. They can start asking increasingly important questions. What is the impact of machine vibration on the quality of the widget? Is there a relation between humidity and machine vibration? How does that vibration change over time and impact quality? Does the vibration of that machine get so strong after producing 100 widgets that I need to shut it down rather than keep running it and producing faulty products?
Smart management teams are understanding that they can deploy Industry 4.0 concepts to bend the cost curve and improve operations. Many leaders have already done this successfully before with lean, outsourcing, and automation. The future represents another turn of the crank.
Helping manufacturers prepare for the future
The real game changer is how to help manufacturers make sense of their data. In our view it is important to understand the context of the data variables and have the right analytical tools and capabilities. Often this requires experience to help manufacturers drive outcomes.
Manufacturers we work with are looking for tools based on machine learning and AI to integrate data from a variety of structured and unstructured sources to spot patterns. This includes orderly data in spreadsheets and ad-hoc data found in maintenance orders, etc. Increasingly, leaders are gathering visual or acoustic data and integrate this into data models. Advanced AI and cognitive technologies allows firms to process all this information and identify outcomes related to cost drivers like downtime, quality and resource optimization.
What are manufacturers missing by not pursuing Industry 4.0?
In our experience, most manufacturers understand they are sitting on a gold mine of data about their operations. Equipment on the factory floor has been producing data for decades in some cases. And big data and analytics have been around for a while. What is new is the industry’s ability to process all of this data and decipher the patterns.
In failing to pursue Industry 4.0, firms are missing opportunities to use the data from their operations to better understand equipment failure, quality, and resource optimization. IBM is building solutions oriented around these three areas to help manufacturers capitalize on Industry 4.0 and reinvent their options. We want to help firms move their operations into the 21st century and help them do more with the information that they have.
Don’t wait. Start today.
The biggest challenge with Industry 4.0 is separating the concept from the execution. This concept is overwhelming to many firms. When we speak to our customers we increasingly advocate starting tactically. What can you do today to start down the right path? What are your pain points around concepts of equipment downtime, quality, and process optimization? How are these pain points unique to your industry?
- Reducing asset downtime. There can be a high cost of downtime for firms running capital intensive equipment. Near term projects include finding ways to incorporate equipment performance data to predict failure and build predictive maintenance plans.
- Improving quality. Some firms – particularly high volume or precision manufacturers – experience high costs related to quality. The cost of scrap or rework is often extensive – and in the case of volume manufacturing a quality defect will quickly be reproduced across a large production run. These firms look for solutions that can quickly spot defects, categorize that defect, and understand the root cause.
- Driving process optimization. Other firms look for opportunities to ensure operational efficiency in process intensive industries. In sophisticated process manufacturing, complexity and high operator turnover can lead to costly deviations and high raw material usage or energy consumption. These industries look for solutions that can understand variables and help plant operators optimize efficiency.
With pressures increasing for manufacturers one thing is increasingly certain: it would be a mistake to underestimate the role data and analytics plays in advanced manufacturing. Increasingly we believe the operators that growth and thrive will be those that embrace the concepts behind Industry 4.0 technologies and are able to translate these concepts to tactical projects. Start fast. Start now.
To learn more about how you can reduce downtime and improve quality with Industry 4.0, watch this webinar.
For specific solutions around optimizing plant performance around insights from assets, go here.
Also check out our solutions around product and process quality.