Driving Manufacturing Improvements with Edge2Web Factory Insights and AWS IoT SiteWise
By Chris Keller, VP Product Development – Edge2Web
By Eddie Budgen, VP Customer Success – Edge2Web
By Thomas Cummins, PhD, Sr. Partner Solutions Architect, IoT – AWS
To quote renowned management consultant Peter Drucker, “If you can’t measure it, you can’t improve it.”
Nowhere is this credo more relevant than discrete manufacturing, where efficient and effective execution are the foundations on which market leaders thrive. Although discrete manufacturers prioritize a variety of metrics based on the nature of their products and markets, three core KPIs are common to all factory operations:
- Availability: Are my machines and related assets available when we need them? What is our downtime profile by asset, line, site? What are the root causes of downtime?
- Quality: Are we producing consistently good products? Which are our best and worst producing assets?
- Performance: How are our factory assets performing relative to their design speed? What causes poor performance? Do we have excess capacity that can be tapped to grow the business?
Overall equipment effectiveness (OEE) is a manufacturing best practice that quantifies the above KPIs and provides a data-driven foundation for continuous measurement and improvement. Most discrete (and many process) manufacturers have OEE on their OT/IT project planning shortlists.
Industrial cloud service platforms like AWS IoT SiteWise, which can be used to acquire and store the data needed to compute critical manufacturing metrics, are accelerating the implementation of OEE applications.
In this post, we identify the tasks required to stand up an instance of Edge2Web Factory Insights on AWS IoT SiteWise. Edge2Web is an AWS Partner and software-as-a-services (SaaS) company whose products are available via AWS Marketplace.
Edge2Web delivers low-code application development tools and solutions to the industrial Internet of Things (IIoT) market. Its solutions enable customers to rapidly deploy game-changing apps that run on open IIoT platforms such as AWS IoT SiteWise and Siemens MindSphere.
Configurable and Extendable
Historically, commercial OEE solutions required a “forklift” implementation project spanning many months (or more). Scaling application usage across sites required significant customization to accommodate operational differences.
Figure 1 – Edge2Web Factory Insights – OEE Summary Scorecard.
Although OEE KPIs are fairly simple to compute, the underlying variables—shift schedules, reason trees, asset groupings, performance thresholds, and the like—are highly specific to each organization (and even different sites within the same organization). Thus, scalable OEE solutions must be configurable by plant data engineers if the resulting KPIs are to have meaning for floor operators, supervisors, and managers.
Factory Insights is a configurable manufacturing intelligence solution that reduces OEE implementation timelines from months to a few weeks and greatly simplifies solution scale-out across multi-region, multi-site operations. Factory Insights was built using Edge2Web’s low-code application development tools and can be easily extended using those same tools.
Below is an architecture diagram of the Edge2Web Factory Insights solution deployed for a single customer tenant.
Figure 2 – Factory Insights architecture diagram.
Easy OEE with Factory Insights and AWS IoT SiteWise
As summarized in the table below, implementing Factory Insights on AWS IoT SiteWise requires a few different activities, some of which are performed by Edge2Web and others by the customer and/or systems integration (OTSI) partner such as Engineering USA.
The steps are roughly sequential:
Figure 3 – Factory Insights solution setup.
Step 1: Provision
A customer acquires a Factory Insights subscription via AWS Marketplace, and provides Edge2Web with the information needed to provision the customer’s AWS tenant.
Once provisioned, a customer administrator can sign into their Factory Insights tenant. The system then guides the administrator through the connection setup process, which is done in two steps.
The first step in the process is to download the Factory Insights template via AWS CloudFormation and install it via the AWS Management Console. This configures a Factory Insight tenant’s access to AWS IoT SiteWise and Amazon Simple Storage Service (Amazon S3).
The second step is to verify the connections in Factory Insights. Once the connections are verified, admins and/or consultants can use Factory Insights tools to complete asset modeling and app configuration activities.
Step 2: Model
Before factory data can be used in AWS IoT SiteWise, an asset model must be created. The asset model is typically a hierarchical representation of factory asset types. A commonly used asset model is the ANSI/ISA-95 equipment model.
Factory Insights includes asset utilities to assist in creating asset models in AWS IoT SiteWise, and then rapidly populating those models with asset instance data.
If a customer is already using a commercial asset management application—for example, the OSI PI Asset Framework—a plant data engineer (or OTSI consultant) can export asset model metadata and asset instance data into CSV-formatted files.
Factory Insights’ asset utilities can import the CSV-formatted asset data and automatically build and populate the equivalent asset hierarchies in AWS IoT SiteWise—a huge time savings.
Similarly, you can provide CSV-formatted files to load your asset instances and build hierarchical relationships for some or all assets. This process can be repeated to add new asset models and instances as usage scales across the enterprise.
Step 3: Ingest
Having acquired the requisite Factory Insights subscriptions, and created/populated asset models within AWS IoT SiteWise, the next implementation step is to acquire plant data (machine operating states, product quality counters, part number) and ingest them into AWS IoT SiteWise.
This is the data Factory Insights uses to compute and visualize OEE (and related) KPIs. Customers have flexibility to ingest data into AWS IoT SiteWise in a number of ways, including by using partner software solutions or via AWS IoT SiteWise Edge. The data ingestion task is typically performed by a plant data engineer or OTSI consultant.
Step 4: Configure
Although the math to compute OEE and related metrics is fairly simple, the practical application of OEE in a typical manufacturing organization requires deep operational intelligence. Otherwise, the resulting KPIs will have little meaning (or value) to machine operators, floor supervisors, and plant managers.
To address this critical requirement, plant data engineers and/or consultants can quickly configure the settings that enable Factory Insights to compute KPIs that are instantly understandable and actionable by plant users.
Available settings include:
- Shift schedules: A scheduling interface allows the configuration of each site’s operating schedule. Factory Insights uses the schedule settings to compute and visualize KPIs for current shift, previous shift, and other commonly-used time periods.
- Reason trees: A visual user interface (UI) that enables plant data engineers to define hierarchies of machine operating and downtime reasons. Factory Insights’ Reason Manager includes reason templates based on commonly-used time categories, such as full production, planned downtime, unplanned downtime, waiting downtime, performance loss, and quality loss.
- State maps: A visual UI that enables the mapping of the codes reported by plant automation devices (machine PLCs, for example) to user-defined reason trees. This mapping enables Factory Insights to automatically convert machine codes to understandable text labels when grouping and visualizing an asset’s availability metrics.
- Asset groups: Although some organizations prefer KPI tracking based on their assets’ defined hierarchies (like ANSI/ISA-95), many also require reporting based on custom machine groupings. Factory Insights provides a visual UI for creating and maintaining an unlimited variety of asset groups to meet this advanced requirement.
- OEE configuration: In addition to shift, state, and asset settings, plant data engineers and consultants also require functionality to set the thresholds and color schemes for KPI reporting. For example, a KPI value for machine availability above 90% can be configured to display using a green color in the Factory Insights scorecards and dashboards. Related OEE configuration settings, such as how a machine acquires quality counters and its design speed unit of measure, can also be easily controlled through the OEE configuration in Factory Insights.
- Team settings: Most organizations prefer to limit end user access to relevant assets. Factory Insights provides a settings UI that simplifies the creation of custom user groups, and the assignment of data access and action policies based on those groupings. This powerful functionality ensures users have visibility to all of the rich performance metrics they need while limiting access to only the data they are allowed to see. It also controls the actions specific user groups may perform (read only, edit counters or reason codes, change application settings).
Factory Insights’ application settings enable the application to be configured to compute and display performance KPIs that are instantly usable in a single plant or across a large, multi-site operation. The configuration activity can be completed by in-house data engineers and/or with the help of an OTSI consultant.
Step 5: Extend
Although Factory Insights provides critical KPI reporting, some organizations need additional functionality that’s unique to their operations.
For implementations requiring custom functionality, Edge2Web provides a bundled solution that includes the Factory Insights application and Edge2Web Director, an advanced low-code industrial application development solution. Factory Insights is, itself, a native Director application.
Using the Director bundle, developers can rapidly add custom application modules to Factory Insights’ core functionality. The Director bundle includes a visual menu editor that enables custom app extensions to be added to the Factory Insights menu, providing end users with a seamless, integrated user experience.
Edge2Web Factory Insights provides advanced manufacturing intelligence based on an open IoT architecture.
The solution can be implemented in a fraction of the time/cost of traditional manufacturing execution system (MES) and manufacturing operations management (MOM) applications, and delivers critical KPIs to plant operators, supervisors, and managers in a form that’s instantly understandable and actionable.
Key benefits include:
- Computes and visualizes popular KPIs, such as OEE, OOE, TEEP, MTBF, MTTR.
- Improves machine availability by quickly identifying downtime patterns and root causes.
- Improves product quality across machines, lines, areas, and sites, and enables operators to manually adjust quality counters.
- Tracks manufacturing performance by asset, shows the impact of planned downtime, and identifies hidden production capacity.
- Reduces time-to-deployment from months to weeks.
- Leverages AWS IoT SiteWise for plant data acquisition and storage, combining advanced application functionality with an open, democratized IoT data platform.
- Delivers insights tuned to each site’s schedules, terminology, processes, geography, and more.
- Secure, fast, and highly scalable. Infinitely extendable using Edge2Web’s low-code development solutions.
Overall equipment effectiveness (OEE) and related KPIs are an important tool for measuring and improving machine availability, product quality, and manufacturing performance.
Edge2Web Factory Insights is a commercial SaaS application that runs on AWS IoT SiteWise. It is highly-configurable, compressing the time-to-implementation at a single site or across multiple sites and regions. Built using Edge2Web’s low-code tools, Factory Insights’ core functionality can be easily extended using those same tools.
This post discusses the steps involved in implementing Factory Insights on AWS IoT SiteWise, and summarizes the benefits delivered by the solution.
Learn more about Edge2Web Factory Insights and sign-up for a free Factory Insights Sandbox account to test drive the application. You can also watch this Factory Insights intro video and get started via AWS Marketplace.
Edge2Web – AWS Partner Spotlight
Edge2Web is an AWS Partner that delivers a low-code platform for rapidly developing and deploying a wide range of industrial IoT applications.