“Knowledge is power,” the infamous quote attributed to Sir Francis Bacon comes to mind when reflecting on Industry 4.0 and the promise of more knowledge and insights. However, while Additive Manufacturing (AM) is creating piles and piles of data, how much insight and actionable knowledge is actually available? Without software that drives positive action, we cannot claim to be harnessing the power of all that data.
The Need – The AM Practitioner
Homegrown spreadsheets and forms, dispersed file sharing locations, part requests via email with no one on point, not to mention, loads of data. Despite best of intentions, even the most organized person can get overwhelmed by coordinating and recording the AM workflow. For us, that breaking point came when a very complex, homegrown AM part request online form was being “phased out”. Bringing up the idea of recreating it in yet another internal platform not really built for the job and likely to be phased out in 3-5 years anyway, was just not an option. Enter in the Manufacturing Execution System (MES) solution, particularly, MES solutions built for the Additive Manufacturing workflow.
What is it?
The term Manufacturing Execution System (MES) was first coined in 1992 by AMR Research and can be defined as “computerized systems used in manufacturing to track and document the transformation of raw materials to finished goods” (McClellan, 1997). These types of systems are well integrated into the fabric of manufacturing, and their purpose has even been standardized by ISA, The International Society of Automation, through the introduction of the “ANSI/ISA-95 Enterprise-Control System Integration (ISA-95)” standard. The ISA-95 standard defines the integration of enterprise and control systems, defining common terminology, outlining application boundaries, and defining information sharing between systems. The basic structure of the ISA-95 standard, shown in Figure 1, positions Manufacturing Execution Systems on Level 3 in the hierarchy between the physical manufacturing plant with its sensors and controls and the enterprise level business-related activities required to manage a manufacturing process.
ISA-95 Part 3 defines the scope of a MES to include management of the following information:
- Production, Maintenance & Quality Operations
- Material handling & Inventory
- Other supporting activities, such as security, information, configuration, documentation, regulatory compliance, and deviations
To scale to series production of any kind, it is advantageous to have systems in place that cover this scope. Not only are you more likely to keep your workforce and their sanity, but it should enable other business benefits like lower lead times, better asset utilization, increased visibility, quality, and traceability, and better cost through realizing these efficiencies.
Why does it need to be tailored to AM?
MESs have been around for over 30 years, but series production of metal AM parts only started becoming more common in the last decade and is still in its early stages. So far, most of the big MES players have not integrated AM specific considerations into existing platforms. The needs of the AM manufacturing community have been met instead by AM-tailored MES solutions. These systems all have their own strengths and weaknesses, and with so many different business models utilizing AM, it is hard to create a one-size-fits-all product. There are some unique attributes of AM that make AM-tailored MES solutions worth considering.
Additive Manufacturing is considered one of the pillars of Industry 4.0, and it fits right in with most machines generating loads of data. Too often, the data is collected, maybe stored, and rarely reviewed. Instead of generating insights into quality, process improvements, and traceability, many users generate terabytes of unused data. Of course it is necessary to have an MES system with this functionality and machines that are connected to leverage the data for insights and decisions.
Additive Manufacturing sells the promise of enabling localized or “distributed manufacturing” but managing multiple production sites is complex. An MES can act as a central hub for relatively seamlessly managing jobs based on machine and material availability as well as end-use location.
A Need for Enhanced Traceability and Visibility
Possibly the most critical function an AM-tailored MES can play is providing traceability and visibility to the process controls. To illustrate the benefits of using an MES to control the AM process and produce qualified parts, we will walk through an AM process overview and potential MES features that help trace process and quality controls.
Powering AM Part Qualification
Consistency, predictability, and repeatability are critical to qualifying AM parts for production use, especially in highly regulated industries. Formerly manually managed in spreadsheets and other user-intensive tracking methods, MES systems can automate traceability for process control and, in some cases, intelligently close the quality loop.
This often begins with the early stages of production such as qualifying equipment for production use. Typically accomplished by a series of builds of coupons that satisfy minimum material and mechanical testing requirements spread over the entire build volume, qualifying equipment generates a lot of data. Data types that are generally important to additively manufactured material include but are not limited to: density, strength, hardness, fatigue, dimensional accuracy, and surface finish. Capturing this data with certain MES controls is essential for analysis and correlation to build variables such as material, build parameters, and equipment settings. Having the ability to trace a qualification coupon’s serial number to a specific build that may have had an anomaly becomes essential to understand and correlate data to certain build conditions.
Similarly, material lot traceability becomes an important factor in such an equation and should not be overlooked. Material lot traceability can be simple and straightforward, or a complex and tedious task depending on level of criticality of production. Added complexity arises when virgin versus recycled feedstock material, mixing of lots, and degradation rate of the material are incorporated into requirements. Currently MES developers are working to make this a much more graphic and automatic process with as few user inputs as possible. This is an instance for which attaching feedstock material sample test results at the appropriate time in the mixing and recycling process becomes crucial for root cause investigation and resolution. Controls that address these concerns are manual or automatic prompts for initial build information when a build file is prepared and digitally sent to the production floor, the laser parameter set assigned to that build, original material certification, post-build event input (such as build interruptions or a post-build feedstock material sample test result), and lists of the unique coupon serial numbers delineated with their correlated test results in a data repository.
Process Analysis, Improvement, & Prediction
Whether it be to develop operational parameters for a new material or establish a better understanding of the process window in which qualified working parameters sit, certain MES controls can help paint the picture of where those boundaries lie. In this stage of qualification or process improvement, in-situ monitoring build data is essential for gauging the success of a set of operational parameters. Operational parameters generally include all build parameters, machine settings, and feedstock material.
An optimized MES control will assign a build’s in-situ data automatically to the unique build identifier once it is complete. In-situ data often includes layer images that may have had an event that triggered a photo capture, build plate temperature, build chamber temperature, build chamber atmospheric data, and so on. More sophisticated in-situ monitoring may include thermal maps of coupons and parts that identify inconsistent thermal profiles and ultimately potential defects. In this case the assignment of in-situ images, melt pool, or thermal profiles by the MES to a unique build identifier is the mode of control. To take a step further, many MES developers are starting to incorporate machine learning once they are added to a given data repository. Machine learning aims to take raw data and automatically correlate it to certain outcomes, thereby notifying engineering of events that may result in a defect that would otherwise have to be caught by a subsequent inspection step.
It is through these control methods afforded by a robust MES a functional data repository starts to take shape. Enabling dynamic querying of data points and corresponding events is essential for tightening process controls to define a fixed process that can be qualified for production. Once a consistent data set is produced, statistical process control can be maintained for future production. A MES gives you the tools to prove that you can do it again and again.
Knowledge is Power
Successful MES implementations are a huge leap from the homegrown spreadsheets of most AM users’ beginnings and are a critical maturation of the technology to broaden adoption and enable controlled series production parts. As MES implementations grow and AM specific software platforms mature, AM practitioners are able to truly harness the power of knowledge… created from all that data.
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