By Lance Fountaine – Manager, GPP Manufacturing Solutions
I was never very interested in owning a GPS system. As a kid growing up in the ‘70s and ‘80s, we were taught to read maps and make the necessary decisions based on the current version of static information. Over time the information source would evolve and we either relied on outdated information or bought a new map. Like many others, however, I was good with maps and gained a sense of pride in getting there the first time without making a wrong turn and beating the rest of the crowd.
Of all people to change my perspective, it was my technology challenged father. While traveling in Florida, he showed me his new GPS unit. I knew of the mapping functionality, but I had never been exposed to the new satellite feedback capabilities. The device not only had access to accurate, up to date maps and travel information, but also had real time traffic and construction feedback capability. Needless to say, he beat me to our destination. This was certain to change my mind set.
In today’s world of information, historical and real time data is prevalent in so much of what we take for granted in our daily lives. We find it in airports, on our cell phones, in our banks, and in many other applications; and its breadth of use continues to grow. These are ‘SMART’ concepts. Although today many consider these concepts only a luxury of technology, tomorrow the world will start to consider them an expectation that is essential for improvements in process performance and capability.
‘SMART’ in Manufacturing:
So what about the world of manufacturing? The challenges to stay competitive as a manufacturer are never ending. It started with the labor market and the perceived cost advantages of offshore resourcing. In more recent years, the challenges to long term manufacturing sustainability have expanded to include environmental and financial regulations, raw material supply chains and energy constraints. Now, more than ever, improvements in process optimization and manufacturing performance are essential for competitive advantage in the marketplace.
So what exactly is ‘SMART Manufacturing’? In an attempt to provide a short and concise definition, it is the integration of data with process expertise to enable proactive and intelligent manufacturing decisions in dynamic environments. The concept is not completely new as there have been pockets of success in many industries. This is probably most notable in electrical power distribution where the ‘SmartGrid’ concept is continuing to evolve into a comprehensive strategy for supply and demand. The lesson to be learned is how to apply this same concept to the optimization of production and the management of the manufacturing supply chain.
The successful adoption of ‘Smart Manufacturing’ requires three critical components; Technology, People and a well defined Operating System.
The Technology of ‘Smart Manufacturing’:
Nearly every modern manufacturing facility has some level of process control and shop floor functionality implemented within the location. The gaps in current capability are not the result of a lack of measurement or control, but instead related to a limited understanding of process history, interdependencies and common definition. Without the ability to correlate data and model performance, efforts to continuously improve the overall process are not reaching their full potential.
It is the integration of the existing instrumentation, process control and shop floor systems that is the key technology enabler for the successful implementation of ‘Smart Manufacturing’. This integration goes well beyond just simple communication between devices, and instead hinges on a comprehensive enterprise and facility data model. This data model stores historical performance, documents relationships and correlations, and facilitates common information rollup and aggregation. It is also a model that can easily be adapted to accommodate both location and enterprise information needs. Figure 1 shows the detailed architecture of the ‘Smart Manufacturing’ environment.
Technology can also be introduced to improve information consumption through the use of wireless networks, portable devices and visualization tools. These types of solutions can help ensure that the right information is provided to the right people at the right time.
Figure 1: The ‘Smart Manufacturing’ Architecture
For more detail on the technical architecture, please see the Appendix: ‘Smart Manufacturing’ Solution Design.
‘Smart Manufacturing’ Success through People:
Technology by itself cannot resolve all of the ongoing challenges of a manufacturer. As in any business, the success of manufacturing also relies heavily on its people. Over time the human resource requirements may change, but it is still fundamental that people drive the successes. As automation, process control and information technology have helped to modernize and evolve manufacturing processes, it is still the human asset that innovates and helps make the next process step change.
Unfortunately, innovation is too often thought of as only a breakthrough in technology. Most innovation, however, truly consists of small process improvements which, if implemented properly, will be locked in for improved efficiency and/or quality.
‘Smart Manufacturing’ provides users with a common toolset for collective innovation. The environment is designed to be used by all levels of the organization including operators, supervisors, process engineers, department managers and even executive leadership. With the ability of strong employee engagement, there will almost certainly be an increase in process innovation. Personal validation through recognized contribution is one of the most powerful drivers for success in any business.
Besides the significant benefits that will be realized through collective innovation, there are also several other secondary people advantages that can be realized through ‘Smart Manufacturing’. With a common and well defined information environment, the organization will be better equipped to handle employee attrition and training. In addition, the standard environment will also allow for stronger collaboration among sites, especially across those locations that utilize similar process technologies.
Finally, adopting ‘Smart Manufacturing’ will eliminate some of the non value added work that is so prevalent today on the manufacturing shop floor. With good vision, strong solution design and continuous improvement, much of the manual data entry and paper routing can be eliminated or significantly reduced. This will allow the workforce to dedicate more time to productive operations or value added work activities.
‘Smart Manufacturing’ Enabling the Business Operating System:
As we outline the technology and people benefits associated with ‘Smart Manufacturing’, it is equally important to recognize its value as a key enabler in expanding the capability of the plant operating system. To completely embrace the concept, manufacturing organizations will need to initiate a change in mindset.
Maybe the most substantial benefit of the ‘Smart Manufacturing’ program is its ability to improve the measurement system. By having real time trends available online, operators and process control systems will have improved capability to make near real time decisions to better manage the process. This process optimization will reduce the number excursions, improve operational efficiency and provide better quality. In any plant operating system, measurement is one of the key components for success. Figure 2 shows an example of a real time operator suggested action to better manage the peak use of auxiliary energy at a manufacturing facility.
Figure 2: A real time operator suggested action to better manage the peak use of auxiliary energy at a manufacturing facility
A second benefit that can be realized in an operating system that is enabled with ‘Smart Manufacturing’ is the automation of KPI calculation, reporting and root cause analysis. In nearly every enterprise business there is strong interest in developing common KPI metrics for performance analysis and power of comparison. Without ‘Smart Manufacturing’, much of this data is manually collected, calculated and reported. There is heavy reliance on people in a process that is prone to error and plagued with many inconsistencies. In addition, there is often little or no ability to drill down to contributing factors as a means of root cause analysis. This often results in time consuming and high cost speculation by one or more groups of experts. ‘Smart Manufacturing’ helps reduce the costs of KPI calculation and reporting, and facilitates any related problem solving activities. Figure 3 shows an example of the presentation of automated daily KPI with drill down to real time.
Figure 4: Real Time Data Accessed through Drill Down from Monthly Dashboard
Finally, a third operating system benefit that can be realized with the deployment of ‘Smart Manufacturing’ is the ability to adopt and rapidly transfer ‘best practice’ innovations across the enterprise. Within the ‘Smart Manufacturing’ environment, it is very important to segregate ad-hoc development and experimentation from established enterprise standards. While it is critical for employees from all levels of the organization to innovate, the enterprise must recognize and approve ‘best practices’ standards. Once adopted, these standards will be propagated across the entire enterprise to quickly leverage the associated benefits to all operating locations. Figure 5 shows an example of a ‘best practice’ development that can be rapidly transferred across multiple operating locations.
Figure 5: An Example of ‘Best Practice’ Development for Transfer
Adopting ‘Smart’ concepts in manufacturing can become a key competitive differentiator in efforts to overcome the many challenges facing today’s businesses. By leveraging technology and enabling people within their plant operating system, manufacturers can better leverage innovation and ‘best practices’ to help lower costs, optimize the process and improve product quality.
The world of manufacturing is changing…and ‘Smart Manufacturing’ will be a key initiative to help drive future success.
Appendix: The ‘SMART Manufacturing’ Solution Design:
The purpose of this appendix is to highlight the technical design aspects that need consideration in the development of a comprehensive ‘Smart Manufacturing’ environment.
Please reference the architecture drawing included as Figure 1. There are four primary technical components that need to be included in the ‘Smart Manufacturing’ design. They are as follows:
- Process Data Collection and Storage (Historian)
- Common Manufacturing Execution (MES)
- Manufacturing and Business Intelligence (MI / BI)
- Integrated Data Model
Each of these technical components needs to be given independent consideration based on the specific nature and current condition of your manufacturing enterprise or location. These considerations will be outlined in detail below.
Process Data Collection and Storage (Historian):
The purpose of a historian is to collect detailed process data and store it into a time based historical database. Although there are a number of vendors who provide historian functionality, the two key technical aspects to consider when selecting a solution are its network connection capabilities and ease of data consumption.
The primary level of connectivity is to the process. This connectivity requires direct linkage to process equipment such as instrumentation, PLCs, HMIs, SCADAs, etc. The challenge in establishing this connectivity is the significant diversity that often exists in process equipment. In many enterprises, there are potentially hundreds of different devices that monitor and control the process. It is critical that the selected historian is able to connect to all of these different devices to enable a comprehensive ‘Smart Manufacturing’ environment.
A second level of connectivity that is needed for the historian is the linkage to the MES and ERP transactional databases. This will allow for two way data interfacing between the process and shop floor, and also enable the automatic calculation and population ok KPI and ERP data.
In addition to connectivity, the historian also needs to allow for ease in the consumption of data. This not only includes the proprietary query and visualization tools that come with the historian product, but also its ability to allow generic integration through standard tools and programming environments. Because ‘Smart Manufacturing’ needs to be capable of aggregating and analyzing data from many different sources, data access cannot be restricted or limited to only the proprietary toolset.
Common Manufacturing Execution (MES):
Manufacturing Execution Systems (MES) have been recognized for many years as an essential toolset for managing operations on the shop floor. Although some manufacturers may suggest that they do not have an MES solution, nearly all use some form of people, paper, spreadsheets or applications to manage production from point of order entry to point of finished goods. These solutions include functions for scheduling, quality management, production reporting, equipment monitoring, etc. In a ‘Smart Manufacturing’ environment, there should common applications supporting the MES function.
The architecture for MES applications is generally pretty standard. It consists of a client based application with a relatively standard transactional database backend. Nearly all MES applications need either significant configuration or development to meet the very specific shop floor needs of the manufacturer. The most critical design consideration that needs to be addressed is whether to buy a vendor supplied package solution or develop a custom application. Both approaches have their advantages, but the decision should really be based on the availability of a comprehensive solution that truly meets your needs. If your processes are fairly unique, sometimes the configuration of a packaged solution can be more difficult, costly, and less effective than a custom solution. In many cases, a hybrid model is the best solution. This approach utilizes vendor packages for common functions and allows custom development for unique functionality.
Whatever MES solution strategy is adopted, it is essential that there is strong integration with both the historian and ERP databases. The ‘Smart Manufacturing’ concept relies on the automation of data summary, calculations and transfers. This minimizes the reliance on people and improves the accuracy and timeliness of reporting.
Manufacturing and Business Intelligence (MI / BI):
The most critical design considerations for establishing a manufacturing and business intelligence strategy are the ability to access multiple data sources and to present this information in a standard, non-proprietary toolset. The challenge that faces so many businesses today is deciding exactly how to accomplish this objective. With so many vendors advertising their own proprietary solutions, and a lack of understanding of manufacturing and business data structure, there are often many conflicting and confusing approaches that are being propagated throughout the enterprise. Two steps need to be taken to overcome this challenge. First, a generic environment needs to be established for the presentation of dashboards and reports. Second, there needs to be an increased focus on the development of a comprehensive data model. We will deal with the second point in our final topic on the Integrated Data Model.
It is not difficult to design a generic environment for the presentation of dashboards and reports. There are, however, certain criteria that are essential for success. First, the functionality should almost certainly be web based and allow access from many different devices including PCs, laptops, thin client, smart phones, etc. Second, it should also be easy to use (leveraging the data model) and allow end users to develop their own ad-hoc queries and analysis. Third, and perhaps most important, the environment should allow for the secure segregation of the standard ‘best practice’ dashboards and reports from the individual ad-hoc analytics. Intelligence is a critical component of ‘Smart Manufacturing’ and the concept cannot be a complete success without recognizing its value and importance to the enterprise.
Integrated Data Model:
The final, and perhaps most important, technical component that is required for a comprehensive ‘Smart Manufacturing’ environment is an integrated data model. To be clear, the purpose of this model is not to replicate any data. Instead, it has three primary objectives. First, it is designed to provide a visual and logical structure with dynamic reference to the source data. Second, it is modeled to recognize the correlative relationships between many of the established data elements. And third, it is developed to provide automated information aggregation and rollup capabilities for the critical business KPIs.
The toolsets to design a visual and logical data model are relatively new in the marketplace. The most fundamental deliverable of the toolset is its ability to define data elements that are capable of dynamically referencing source information from multiple databases. In most cases, it is recommended to structure these data elements in an asset format. Each data element can then also be defined as enterprise common, technology common or site specific. This helps ensure the solution meets the needs of the enterprise as well as those of the location. The visual and logical data model allows users to more easily locate the data that is needed and to better comprehend the scope of the information that is being consumed.
An added benefit when establishing the visual and logical data structure is the ability to define some level of correlation among the many different data elements. As a starting point, perhaps the easiest correlation to define is that between the KPIs and the defined assets. By adding KPI elements to the logical data structure, these initial correlations can be established for further drill down analysis capabilities.
When adding KPI correlation to the data model, it is also important to recognize the ability and benefits of automated data aggregation and rollup. All KPIs are based on some level of source data. Although there are certainly examples of manual entered source data, many of these elements are from an online source. In either scenario, however, it is critical to understand how that source data is calculated or rolled-up into a summary KPI. In some cases, these KPIs are even calculated and summarized in many different frequencies (i.e., daily, weekly, monthly). As a result, it is important to establish clear calculation and rollup procedures as part of the data model. By using an automated calculation process, the solution will ensure consistency and eliminate errors.
It is also very important to recognize that the data model, as all other components of ‘Smart Manufacturing’, is a living part of the environment. It will never be perfect, and will always be evolving. New data points and KPIs will be required over time, and changes will have to be effectively controlled to ensure the component maintains its integrity. A good change management process is certainly an essential requirement for the success of a ‘Smart Manufacturing’ program.