(84) Stages of IIoT Value Curve for the manufacturing industry

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Products, Platforms, Business & Innovation in Industry 4.0/IIoT

11 min readAug 1, 2019

A well-designed Industrial Internet of Things (IIoT) system helps manufacturers analyze all the raw plant information and convert it into business value, such as improving production yields, optimizing maintenance costs, maximizing line productivity, and tracking resource use in real time to meet business, production, and regulatory objectives.

IIoT adoption is a maturity progression where IoT companies realize increasing levels of benefit as they expand from basic machine connectivity to advanced approaches including analytics, automation, and edge computing.

In this post, I try to summarize my research on how most of the existing IIoT players navigate the stages of maturity.

To begin with, lets try to list out all the goals a factory owner hoped to benefit from digital transformation:

Increase production yield
Efficiency
Quality
Compliance
Reduce unplanned downtime
Maximizing line efficiency and output
Tracking and automating real time resource usage
Preventive maintenance
Remote diagnostics
Asset tracking
Automatic fulfilment
Compliance monitoring
Strategic asset management
Production quality
Asset optimization
Improving safety
Cost reduction
Optimizing Overall Equipment Effectiveness (OEE)
Customization for customer experience
Increasing uptime and throughput in the plant and closely managing costs

If you were to fulfil these benefits, which goal would you begin with and navigate next?

Jason Shepherd , CTO, IoT and Edge Computing says:

“To get the power of IoT, you need to connect the physical world to the digital, with the evolution typically starting with real-time monitoring for visibility and then moving to optimization through analytics and eventually automation.”

Bsquare’s 5 Stage IoT Value Curve

Bsquare, which is an IoT solutions provider defines five stages of IoT maturity:

Stage 1: Device Connectivity & Data Forwarding

Today, most factory equipment comes outfitted with myriad sensors to transmit a wide array of data. They also have a variety of connectivity options, from plug-in diagnostic reader ports to wireless modules, for delivering data to cloud-based devices. As a result, the average factory streams terabytes of production-relevant each month — ranging from motor operating temperatures to unit counts, product weights to conveyor speeds, motion-tolerance detection to raw materials usage, and much more.

Although IIoT-connected equipment provides the foundational first stage of such data collection and forwarding, merely gathering and storing data delivers little to no business benefit. At a minimum, monitoring and error alerts are required to begin to achieve value from the data.

Stage 2: Real-time monitoring

Monitoring connected plant data begins to provide just-intime awareness of machine and production line conditions. Real-time operating parameters and fault codes can be visualized as graphics, charts, color-coded alerts, etc., on dashboards that are view-able on any cloud-enabled device. So factory owners at headquarters, operators in plant offices, and engineers on the floor can receive notifications when faults are detected, equipment failure is likely, inventory is low, or operating limits are exceeded. Teams can then take appropriate steps to adjust and re-mediate.

While these basic dashboard and monitoring solutions benefit human operators, they lack the sophisticated logic to detect the complex conditions and events frequently found in factory environments. They do, however, provide a starting point for manufacturers to examine and refine the business processes necessary to achieve their desired outcomes.

Stage 3: Adaptive Data Analytics

Analysis of intricate, multifaceted events, using multiple sources of data for context, is where IIoT really begins adding measurable business value. The best solutions use data discovery, machine learning, cluster analysis, and digital modeling to apply complex event processing and adaptive analytics to real-time and historical data from factory and complementary sources — providing detailed visibility across the manufacturing infrastructure. These insights allow plant operators, engineers, and technicians to proactively manage equipment health and optimize production. This reduces the likelihood of unexpected failures and related problems, like production delays and expensive repairs.

Factory data use cases:

Root cause analysis: Identify problems faster, with greater accuracy.
Optimized repair workflows: Guide technicians to improve first-time repair rates.
Condition-based maintenance: Service equipment based on actual usage, conditions, and performance

This ability to detect, alert, and guide equipment maintenance provides high value to any manufacturer seeking to optimize production output. However, the sheer amount of data produced by multiple sources and across entire plants may overwhelm human operators and dashboard systems, limiting the scope of where analytics can provide business benefit. Some form of automation is also needed to help teams respond quickly and appropriately to fluctuating factory conditions.

Stage 4: Automation

Automating the wealth of insight and awareness provided by the adaptive data analytics in Stage 3 allows a manufacturer’s IIoT system to become progressively more intelligent, and capable of delivering greater business benefit. Dynamic rules-based logic can orchestrate complex actions across an organization, including service ticketing and inventory adjustment requests. Machine learning and sophisticated analytics also enhance an IIoT system’s intelligence. For example, it increases data collection and transmission upon detecting an anomalous condition on a production line. The system can then execute a series of automated steps to correct the error, or automatically adjust operating parameters to minimize damage while also notifying a technician of the issue and repair urgency.

In Stage 4, all IIoT processing activities are done over a separate cloud location that is accessible from any mobile or desktop device. Even greater automation can be achieved by moving these automated processing tasks onto the units themselves.

Stage 5: Enhancing onboard intelligence

By embedding the same intelligence and processing capabilities from Stage 4 directly into plant equipment, analytics and actions can be performed right at the network edge, rather than in a separate cloud location. Juxtaposing logic capabilities with source data aboard the machine (rather than transmitting the data from the machine to the logic tools in the cloud) eliminates any loss of accuracy from wireless transmission and conserves cloud data storage and network bandwidth. It also enables many other ways to work with the data and manipulate equipment directly, such as to apply real-time asset optimization and configuration to achieve greater quality control, or to automatically retool production lines.

Stage 5 provides maximum ROI and business benefit from predictive failure, data-driven diagnostics, and device optimization.

Most manufacturers start with less complex projects, such as enhanced visibility or tracking, and progress to more sophisticated processes that require automated or predictive workflows, according to IDC.

Elevate’s 6 Stages of Maturity

Elevat.IoT, an IoT company identifies 6 stages of IoT maturity as shown below

Stage 1: Unconnected

Stage 2: Connected

Stage 3: Serviceable

Stage 4: Intelligent

Stage 5: Optimized

Stage 6: Differentiated

PTC IoT Roadmap Value Curve

PTC identifies the following value curve that all IoT companies should traverse towards.

The Value Chain is usually defined for a particular industry. For IoT as a technology (coming together of technologies rather), it starts with the (bottom up)

Hardware layer : Sensors, Actuators, Chipsets, MEMS
Network layer: Both connectivity layer (PAN: Bluetooth, Zigbee, Wifi, etc), and telecom service layer (Wifi, GSM, 4G)
Platforms: Software platforms that enable IoT.
Cloud / Analytics / Application layer: to make store, visualize and make sense out of data.

PTC came up with another value chain

Siemen’s Mindsphere’s Value Chain

Axeda defines 6 stages of maturity

Level 1: Unconnected

Description. An unconnected organization is looking to make existing processes more efficient and drive higher levels of intelligence from the connected world. There are IoT opportunities in every industry because virtually all electronic and electro-mechanical products can be designed to automatically transmit information about status, performance, and usage, and can interact with people and other devices in real time.

Requirements. At this level, understanding what’s possible and the underlying technologies is critical. Embedded software, network communications, device protocols, provisioning, and real-time data processing technologies combine with advanced Web Services, security, and data management to strain the skills of most IT organizations and development teams. Few companies have all these specialized people on staff, so IoT projects can get stalled or off track — if they are ever started at all. Increasingly, companies are coming to the conclusion that they should focus on their core competency, dismiss the idea of the internal “build,” and conduct an educated “buy” with faster, short-term ROI and time to market.

Implementation. Level 1 starts with planning. The first step is “Getting connected” which is a broad term with different meanings depending upon the environment of the product and the economics of the solution. And while IoT isn’t new, the fundamentals of a connected product initiative are incredibly complex. Basic enablement, network connectivity, security, middleware services, cloud services, application development, and other device management functions are all needs that must be addressed when organizations seek to launch a connected product initiative. Axeda provides the features and functionality to help your organization connect, as well as the infrastructure to support an IoT environment with domain experts and proven cloud services. Axeda also offers Innovation Workshops which will help you define and launch your connected products program and help your key business and technical groups work together to develop a common point of view. After you describe your key business and IT objectives and challenges, Axeda subject matter experts collaborate with your team on the key elements of a IoT strategy, especially as they apply to your current environment. Innovation Workshops are offered at your business location, or at Axeda headquarters in Foxboro, Massachusetts.

Level 2: Connected

Description. Once connected, organizations begin to realize a new means to generate growth and achieve a sustainable service position. Connected product services typically generate a recurring revenue stream, require less fixed capital, and provide potentially higher margins.

Requirements. Connecting products to a network is not always trivial. Keeping up with device proliferation and the numbers and types of devices produced by manufacturers continues to grow rapidly Here, the focus should be on developing a solution that is resilient to change and allows applications to capitalize on, rather than be hindered by, product differences

Implementation. Reaching Level 2 is accomplished by connecting a product to a network (internet, cellular or satellite) and enabling data transmission back to an enterprise server or system for processing. Axeda provides IoT Connectivity Services that include software agents and tool-kits that enable your organization to establish connectivity between products or assets and the Axeda Cloud, while allowing a choice of communication methods and hardware to suit the requirements of any IoT solution. As a result, your organization can connect to any product over any communication channel — cellular networks, the Internet, Wi-Fi, or satellite

Level 3 — Serviceable

Description. Each and every product requires some level of service and support. Service organizations are increasingly adopting remote service solutions to identify, diagnose, and resolve issues remotely. Axeda connected product management applications fit that need in helping to deliver proactive service to their range of devices — improving uptime, slashing service costs, and paving the way for value-added services based on the devices’ data. Requirements. Organizations require a cloud-based application platform and suite of tools to monitor assets remotely login and manage remote content. The solution would handle hosting, security, scalability and have flexible APIs, so that they are unencumbered by infrastructure and can focus on the value of the solution. Implementation. Reaching Level 3 is accomplished by enabling remote access and service. Axeda provides a secure and scalable cloud to process and store machine data and cloud-based applications to deliver remote service. The service includes web-based purpose-built connected product management applications for monitoring, remote login, desktop sharing, software management and remote content distribution.

Level 4 — Intelligent

Description. Here, the focus quickly turns to analyzing the data and developing user-facing tools and applications that facilitate data analysis, provide insights and improve business functions. With the right IoT reporting and BI solution, your company can run reports, query the data, create dashboards, or feed the data into your data warehouse and BI environments. Requirements. Many organizations including Service, Engineering, Finance, Compliance, QA, Product Management, and Sales need visibility into product usage, performance and behavior. The data from the connected products needs to organized and stored in a way that makes it is easy to report on and analyze. Implementation. Reaching Level 4 is accomplished by enabling reporting and analytics. With Axeda Service Intelligence, your organization can easily build and deliver ad-hoc queries, professional reports, and dashboards that articulate success metrics and KPIs, with reporting functionality that demonstrates the value of connected products. With a powerful business intelligence engine and easy-to-use report and dashboard building tools, your organization can understand the “what” and “why” of your IoT data.

Level 5 — Optimized

Description. Organizations who were early in bringing their products online are now realizing that the real “gold” in IoT is taking that data and integrating with enterprise systems such as CRM, ERP, PLM or data warehouses — optimizing critical business processes and essentially “IoT-izing” their business.

Requirements. IoT data must be made available to integrate with other systems. The IoT data must deliver additional value by combining information from connected products with information from other complementary sources and systems to enable people and processes to collaborate and extract even more value. For example, product data flowing through a CRM system can be sent to billing or into a supply chain management system — eliminating error-prone manual steps and providing new sales opportunities for consumable replenishment or warranty renewals. Quality assurance or product management can help enhance product features based on realworld data that shows usage patterns or equipment issues — improving customer satisfaction and streamlining beta programs. The valuable IoT product data — now unlocked — can also guide engineering efforts in building more reliable products with differentiating features driven by customer demand. Implementation. Axeda offers a framework to integrate with business systems by feeding IoT data into CRM/ERP/PLM systems to optimize business processes by enhancing service, billing, sales, inventory management, and product development. The framework includes web services APIs to read and write data as well as a standards-based message queue for asynchronous data transfers. Once integrated with Axeda, IoT data from connected assets, in collaboration with other enterprise systems, can provide visibility and automation across organizations not previously possible.