Industry 4.0, or the Fourth Industrial Revolution, is the combination of various digital technologies—computers, enterprise software, the IIoT, machine learning, and big data analytics— to create a new, fully digitalized manufacturing ecosystem. Like the three industrial revolutions that came before it (steam power, electricity, and automation), Industry 4.0 is proving to be transformational.
The backbone of this new ecosystem is the Manufacturing Execution System (MES), which produces and gathers most of the essential manufacturing data. It also enables decision-makers to deploy changes in products, plans, and supply chains throughout the enterprise quickly based on up-to-date information. MES, implemented as part of an Industry 4.0 manufacturing strategy, turns a collection of disparate operations and into a well-oiled, digitally transformed machine.
Manufacturers who implemented MES reported boosts in net profit margin, improved on-time delivery, and had a 23% reduction in total cost per unit.
Big Data and Software Are Driving Manufacturing Innovation
Data is arguably the most underused resource in the modern manufacturing enterprise. It also represents the biggest opportunity.
MES and IIoT-connected machines generate huge amounts of data, but it is not easy to collect and distribute it all to the right people at the right time. It’s estimated that the average factory generates as much as a terabyte of production data per day. Yet many organizations, especially those with disparate systems, can utilize only a small fraction of that data, and rarely to support actual operational decision-making.
This is why big data analytics software is the perfect partner to MES and a critical component of Industry 4.0 manufacturing. Big data refers to datasets that are too vast for typical database software tools to effectively capture, store, and analyze—which describes most manufacturing databases.
With big data analytics, it’s possible to see trends and correlations in this data that would be undetectable to the human eye or to previous-generation software. By combining big data analytics with the agility of an MES-controlled factory floor, manufacturers are achieving significant performance gains in many areas.
Big data analytics can help grow your operation by:
- Boosting productivity by up to 30%
- Reducing product development and assembly costs by as much as 50%
- Improving quality
- Significantly reducing capital costs
The potential of big data analytics is only beginning to be tapped. Only 17% of manufacturers have reported implementing big data analytics solutions so far, but many more are planning to. Read about the drive to digital innovation.
MES Solutions Are Integral to Digital Transformation
Successful digital transformation is about creating an ecosystem of technology that all works together. Each piece of Industry 4.0 technology is strengthened by the other business systems it communicates with.
MES is central to this scheme because it allows other key systems like ERP and PLM to connect with real-time manufacturing operations, creating a holistic digital approach to complex manufacturing. The tight integration of these critical systems improves time-to-market for new products and product upgrades, among many other benefits.
Industry 4.0 MES integrates with:
The Proactive Enterprise
Integrating MES with ERP and PLM systems creates a proactive enterprise, instead of a reactive one. ERP and PLM are not enough to accomplish this alone. Since they are primarily systems of record, they need integration with an execution system in order to effectively act on any of the information. Once integrated, factory managers can be proactive about ensuring the delivery of on-time, cost-effective products.
Closed Loop Integration
When integrated with both ERP and PLM, Industry 4.0 MES closes the loop between design, production, quality, and resource management, and provides a “single source of truth.” Everyone from the shop floor to the CEO are able to work from the same real-time data. PLM users can easily send engineering changes to the shop floor. Then, as resources are modified, the information is sent to ERP to avoid tedious re-entry of data. Closed-loop integration between ERP, PLM, and MES improves quality and change management across the entire value chain and product lifecycle.
Benefits of PLM-ERP-MES Integration
Make engineering changes during production
Integrating MES helps manufacturers make adjustments during production by combining the systems with inventory information (ERP), and the system with design information (PLM), with the system that builds the component (MES). In addition, MES can share information with other systems when implementing new manufacturing processes or product changes requested by customers. That means that any process or product change can be made in real-time during production anywhere in the world.</p
Improve inventory management
Closed-loop integration gives managers the information they need to make educated decisions based on actionable business data. It can supply the high level of precision over inbound and outbound inventory required for methods like just-in-time delivery and lean manufacturing. It also streamlines workflows by automating most manual tasks— for example, automatic reordering when inventory falls to a set level.
Improve quality control
Predictive maintenance data can be leveraged to make production adjustments in real-time. If there is a quality issue on the floor, MES can send real-time notifications to the other business systems. This ability can minimize the impact of equipment downtime and reduce the manufacturer’s exposure to recalls and quality issues.
Harness IIoT integration
Many modern factories use machines that generate data from sensors and control mechanisms. MES can take all of this information and distribute it to the right systems, which improves all aspects of production: reduced downtime, strengthened supply chain stability, on-time delivery, and more.
Improve data accuracy
Integrating MES with PLM ensures that records match what actually happened during the production process. It creates a closed loop between design and production so that the virtual design matches the physical production. The production data can also be applied to broader continuous improvement initiatives.
The Digital Thread
The Digital Thread is an important concept in Industry 4.0 manufacturing. It is a digital model of everything about a product’s lifecycle: design, manufacture, process, quality inspection, even post-delivery maintenance and operations.
The Digital Thread provides a single source of truth about all aspects of a manufactured product and allows enterprises to model products and processes to gain insights and continuously improve. MES is central to the Digital Thread, not only because it provides the critical manufacturing data, but also because it provides a mechanism for taking what is learned from this lifetime view and feeding it back into design and MES for continuous improvement. This translates into customer value and operational excellence.
Data Accessibility of an Industry 4.0 MES
Data accessibility is a primary goal of industry 4.0 MES. With contextualized and distributed data, executives and managers have the information they need to make the right decisions.
Accessibility includes being able to see the data needed from any tablet, smartphone, or computer terminal. But it also means much more. Manufacturers need clear visualization of data with multi-dimensional and real-time information on process variables. Industry 4.0 MES unifies all data so that executives, managers, and line workers are all working from a single version of the truth, with information contextualized for their use.
Cloud-based applications make it easier to distribute and access manufacturing data. They also lighten the load on technical debt by reducing hardware and ensuring smooth software upgrades. Many organizations need to keep the most sensitive information on premises, so Industry 4.0 MES does not dictate the implementation. It allows the organization to deploy Industry 4.0 software technology on the cloud, on premises, or both, as needed for their circumstances. What results is a flexible solution that takes advantage of cloud solutions while securing the most critical information.
Efficient Data Analytics
Big data analytics demand extraordinary levels of processing power. Industry 4.0 MES allows users to export data to cloud-based big data structures to efficiently distribute operational data. The result is contextualized data that organizations can use to respond to changing conditions.
Data accessibility optimizes production processes by standardizing process improvements. It ensures that business decisions are based on up-to-date production information, with the contextual data to anticipate its impact on the supply chain or product lifecycle. Simultaneously, machine learning enables systems such as MES to keep pace with changes in production.
Part of the drive for Industry 4.0 and digital transformation is to automate the collection, analysis, and distribution of data to make it available for dashboards and accessible to our citizen data scientists to go in and grab it, manipulate it, and do whatever they need for custom, high-value-added reporting.
Dr. Don Kindard, Senior Fellow, Lockheed Martin
The Benefits of an Industry 4.0 MES
Real-Time Data to Inform Real-Time Decisions
Real-time manufacturing data for everyone who needs it is one of the most transformational benefits of Industry 4.0 manufacturing realization. Computers and IIoT machines can be used to continuously process data and provide managers with real-time business insights. For example— if a plant supervisor has to shut down a production line because of a defective part, they can quickly isolate which supplier it came from and issue a corrective action. Instead of spending valuable time searching for the problem, they can access machine information to mitigate or eliminate downtime.
Compliance in Regulated Industries
Compliance regulations are more stringent than ever. Manufacturers need to keep meticulously detailed records of every single component and subassembly, even though most are sent from different suppliers. Industry 4.0 MES enables users to accurately record and search all compliance-related data in case of audits or other traceability purposes. Organizations gain resilience by keeping all traceability accurate and in one place. If production needs to be shut down until a compliance issue is resolved, the right MES is the tool to quickly resolve the problem and prevent downtime.
Quality in an Industry 4.0 World
Quality standards have risen as more manufacturers adopt higher expectations. Industry 4.0 manufacturers need high-quality, innovative products. The cascading effect of closed-loop integration, real-time data, machine connectivity, and process automation all work together to reduce errors, downtime, or any other threat to quality and on-time production.
Industry 4.0 Systems Drive Increased Revenue
Increased revenue is the ultimate result of Industry 4.0 MES. Industry 4.0 manufacturers operate with lowered production costs because of real-time data and closed-loop integration. Compared to the last decade, they have decreased cycle times, faster time-to-market, reliable on-time delivery, and higher production capacity.
Your Road to Digital Transformation
Digitally transformed manufacturers will need new metrics to measure the success of their digital transformation. As expectations rise higher and higher, what was once considered a gold standard of digital technology is now the norm. Industry 4.0 is a revolutionary change, and that means organizations will also need to change how they measure its success.
Speed of Response
With systems in place that are able to monitor machine performance, quality, or maintenance before they occur, speed of response becomes an important metric. Old metrics, such as Mean-Time-Between-Failure or First-Pass Yield, become less meaningful once downtime, out-of-spec production, and production upsets are essentially eliminated. The new focus of attention becomes the frequency and time between issues, and how quickly the organization can use real-time data to isolate production or supply issues.
Speed of Deployment
The best Industry 4.0 MES solutions have timely implementations. New metrics to measure digital transformation success should include some key indicators:
- Engineering change management cycle time reduction
- Reduced out-of-stock delays in production operations
- Increased ability to handle additional product variants
Rate of Adoption
The earliest metric of digital transformation success is to determine how many business processes are digitally enabled, and how effectively it has improved the processes. As companies plan their Industry 4.0 MES implementation, they should define how processes are done pre-digitalization in order to track the number of processes that move to digital and the speed of adoption. Some new adoption rate metrics include:
- Percentage of manual data entry operations eliminated
- Percentage of reporting operations automated
- Percentage of positions that utilize new technology
- Reduction rate of data entry errors
In addition to these new metrics, Industry 4.0 MES can use existing metrics differently. Instead of being used as a metric for improvement, Overall Equipment Effectiveness (OEE) becomes an alarm threshold for manufacturers. For example, a deviation beyond some limit could trigger preventive action, greatly reducing unplanned downtime.
MES at the Center of Industry 4.0 technology
The collective power of Industry 4.0 technology is growing exponentially. Intelligent robots, systems, and people are increasingly linked in a digital ecosystem, where decision-makers at all levels can access the data they need, right now.
Industry 4.0 and MES aren’t just about upgrading to the next new technology. The mission is to revolutionize the way manufacturers work, from the executive suite to the factory floor. And MES is the unifying force that makes this digital transformation a reality.