By David Schultz
One of the activities of migrating from Industry 3.0 to Industry 4.0 is that of digital transformation. A digitally transformed business eliminates most, if not all, of its paper used in its processes. Data from any system is available in real time, along with context, and transformed into information. However, before a business can embark on a digital transformation effort, it needs to understand the benefits and associated costs. While there are many drivers of digital transformation, this article will attempt to answer the question: what are the most important drivers of a successful digital transformation?
While the topic is about drivers of digital transformation, I would like to comment on the features and architecture of a solution (hardware, software, etc.) that supports a transformation effort. There are four key components:
- The technology should utilize open standards.
- Data updates should report by exception, rather than poll response.
- Communication protocols should be lightweight to limit use of network bandwidth.
- Everything should be edge-driven, in that decisions are made as close to the business process as possible.
Driver # 1: Work Order Generation
Those with a background in reliability, like me, will gravitate toward maintenance as one of the biggest drivers of digital transformation. A digitally transformed maintenance and repair department, sometimes referred to as Maintenance 4.0, has a complete digital system for performing work. For example, a downtime event may be due to a failure in a piece of equipment. While a downtime system may capture this event in real time, the subsequent maintenance request is often a manual process. Moreover, the work order system may also require manual input to perform the work.
In a transformed maintenance scenario, the event continues to be captured in real time, but the subsequent notification and work order creation are all done automatically. All of the activities are captured in real time from the initial event, the creation, acceptance and completion of the work order, and the system coming back online. The status of the work is available to anyone at any time.
Driver #2 : Manufacturing Status
When a company receives an order into their ERP system, it leads to the creation of a sales order which is used by the manufacturing area. While some companies may utilize an MES or MRP for their production, it continues to be quite common for a manufacturing process to use paper to manage the order through the process. At the beginning of a shift, a line supervisor has a stack of SOs which make up the daily production schedule. At the end of the shift, all of the SOs are collected, along with batch records and shift report, for processing the next day.
In a digitally transformed business, all of the SOs are processed electronically. If there is a need during the shift to modify the batch order, this can be done quickly. Any issues that occur are available in real time. A person in customer service can check the status of an order and advise where it is in the process. All of these activities lead to tremendous efficiency gains.
Driver # 3: Energy
The cost of energy can be quite high for energy-intensive processes, like petroleum refining or steel manufacturing. This includes electricity, steam, and compressed air. Over the past few years, it has become more common to install electrical meters and flowmeters at additional points in the process. This helps increase the granularity of the measurements made. However, many of these systems do not provide connectivity to other systems, which allow energy consumption to be compared with other process information.
After transformation, all of the energy (electrical, compressed air, steam, etc.) is measured and available to other systems. A common application is to determine how much energy is used in the manufacture of a unit of product. Over time, this data can be analyzed to look for anomalies in product codes, line performance, or shift performance.
Driver #4: Quality
One of the challenges to managing quality in a process is knowing when an issue has occurred as soon as possible. A common event in manufacturing is finding out about a quality issue long after the event, perhaps when the paper shift report was delivered. When this occurs, the quality team is assembled to determine what events lead to the issue. Oftentimes, by the time the cause was determined, and corrective actions taken, another quality issue has occurred.
Transforming your quality processes would have this information available in real time so that corrective measures can be made during production. Similar to energy systems, quality data can be analyzed relative to other process data. Once these patterns are understood, models can be developed to help provide notification before events happen.
Driver #5: Process Upsets
Continuing on the theme of timely notifications, it is quite common to have process upsets occur without the right people being notified. Having information available in real time—and using analytic tools—not only provides notification of process issues, but can help prevent them from occurring in the first place. Furthermore, this does not require many hours spent reviewing all of the process parameters to look for the signs of an impending process fault. It is all done in real time for you.
Driver #6: Analytic Capabilities
As noted above, when process status, process health, and asset health data are readily available in real time, there are many advanced analytics capabilities that can be realized. Processes can be optimized for a parameter, like throughput, while maintaining quality. Assets may be able to have extended operation before maintenance is required. Improving overall operational performance can lead to optimized inventory levels. To be sure, the data in making these decisions needs to be accurate. But analytics capabilities can lead to a significant improvement in financial performance.
Driver #7: Elimination of Paper
Finally, the elimination of paper is somewhat of a bonus driver in a transformation effort. There is no longer a need to print shift reports and batch records. All of this information can be presented digitally, either as a dashboard or as a report that is sent electronically at the completion of the event. Ad hoc reports that were once printed are now shared electronically, too. Raw material is received using scanners and tablets without the need of a printed ticket. All of this saves on paper costs and recycling costs.
As I noted earlier, the are many business drivers for digital transformation. These are just a few. Before you begin, I suggest you determine a business problem that needs to be solved and then start to transform that part. Be sure to have an overall strategy in mind, as decisions made now will impact future capabilities (they are cheaper to change early). As more systems are transformed, the benefits will be readily apparent—and the economic benefits can be used to support more efforts in the future.
This article is a product of the International Society of Automation (ISA) Smart Manufacturing & IIoT Division. If you are an ISA member who is interested in joining this division, please log in to your account and visit this page.
About the Author
David Schultz has 25 years of automation and process control experience across many market verticals, with a focus on continuous and batch processing. He currently works with manufacturers to help them develop and execute strategies for their industrial transformation and asset management efforts. He is the current Vice President for the Milwaukee Chapter of ISA. He is actively involved in ISA’s Digital Twin and AI/ML technical committees. He is also a member of the Society of Maintenance and Reliability Professionals (SMRP) and Project Management Institute (PMI).