Tomorrow’s competitive, successful factories will need to be connected and flexible at levels rarely seen today, says Tebodin, the global consulting and engineering company, in a short whitepaper on The Three Success Factors for the Factory of the Future. In our team discussions, we found that the paper gets many things right. What should manufacturers think about as they aim to thrive in a changing industry by exploring digital business models?
Gaining operationwide, transformative transparence
In a more traditional operation, practices like machine-condition monitoring with realtime data from the internet of things (IoT) can make processes more efficient and equipment more reliable. In the transformative context of Industry 4.0, however, their reach widens. They can help change the way your company makes decisions, positions itself competitively, and manages production.
Instead of transmitting information through a chain of physical and computerized systems and up and down organizational hierarchies, you can use IoT, machine-to-machine communication, data analytics, and other technologies to create a realtime factory. In that factory, every entity connects with every other entity in a web-like data infrastructure, not a linear sequence of elements.
What changes when everybody has access to the information that matters? You don’t just link the shop floor and its industrial machinery to production management and maintenance. You also connect it to production planning and forecasting, procurement, sales, distribution, engineering, quality control, and other business activities.
At that point, using the right tools to help you gain visibility across the entire operation, you can enable effective collaborations and better manage production. Your awareness extends to the impacts and consequences of formerly isolated, almost static processes and events.
When a machine is down or not keeping up with production commitments, you can reroute production to another one. You can also take other actions, ranging from adjustments in vendor shipments to customer communications, to avoid slowdowns, stockpiling of materials, and customer dissatisfaction.
The connected, realtime factory has already proven its effectiveness. As Tebodin points out, analysts confirm that fully connected manufacturing operations can be far more productive according to a number of widely used standard KPIs and metrics, including Overall Equipment Effectiveness (OEE).
Data flows facilitate tomorrow’s factory
The fundamental enablement of Industry 4.0 transformation for manufacturers comes about through information residing in digital systems, buoyed by an understanding of the business value of reliable, comprehensive, and up-to-the-moment data. For production companies, Industry 4.0 is not about acquiring more and newer technology, but about making more connected and strategic use of digital assets – hardware, applications, and data – to run manufacturing operations and other processes.
Data insight from analytics helps companies justify their investments in process optimizations, industrial assets, and digital resources, and provides the understanding that can shape and drive organizational strategy. In the connected factory, data is the universal currency that validates and facilitates business outcomes. In consequence, technology becomes more strategic and more effective in supporting business interests. It is no longer under the exclusive control of IT organizations.
An increasingly critical role for IT
However, IT provides essential enablement for the transformation companies undergo when they digitize their products and update their business models. Tebodin uses the metaphor of the central nervous system to describe the role of IT in the connected factory.
In many innovative manufacturing companies, IT teams and technologies already play this central role in collaboration with the business owners. They use software to control robotic production systems and logistics, or rely on data-driven decision support that relies on information from multiple sources.
Many companies are still very cautious in introducing organizational changes that can take advantage of freely flowing information and digitally enhanced processes. In some more progressive companies, we see multidisciplinary teams organizing themselves with a focus on customer accounts, sometimes crossing organizational boundaries to pursue collaborative design and product development with customers.
Moving toward a lifetime customer engagement model
One aspect of this boundary erosion is that customers may welcome manufacturers’ involvement long after they acquired their machinery. Realtime visibility can greatly augment accountabilities. The vendor may be invited, expected, or committed to perform remote, realtime monitoring of machine assets, maintain them proactively, and help customers’ operators use them expertly and productively. That change in the customer/vendor relationships can also be the beginning of enhancing and transforming products with, or in form of, services – usually referred to as servitization.
As the complexity of machinery requires more advanced and specialized skills to maintain it, this type of extended engagement will become common as companies look to deliver value to their customers. In a digital enterprise, moreover, it may be possible to perform portions of the work, such as machine reconfiguration, remotely. Accessing shared workspaces and resources in the cloud, technicians at a customer site will more easily be able to access documentation and expertise outside of their organization to resolve machine problems or finetune equipment to perform better.
The cloud, enterprise mobility, and digitally enabled processes can all boost the customer focus of machine management and maintenance. People may rely on artificial intelligence (AI) to perform the most timely and efficient maintenance actions and schedule and plan machine production loads, or learn and collaborate with assistance from digitally directed robots.
If you want to discuss tomorrow’s factory and your ideas for it, send me a note at email@example.com.
5 best practices to improve OEE with condition-based monitoring