Internet of Things (IoT) is a concept of connecting devices over the internet. Devices containing sensors are connected to an IoT platform which then retrieves data from these devices and applies analytics to share the information. Industrial Internet of Things or IIoT is a sub-segment of IoT which is used across various industries such as manufacturing, logistics, oil & gas, transportation, energy & utilities, mining & metals, aviation, among others. The IIoT refers to the computers, machines and people enabling intelligent industrial operations using advanced data analytics for transformational business outcomes. IIoT is gaining prominence in industries as it helps to optimize operational efficiency and opens up numerous opportunities for automation, asset management, industrial control, intelligent manufacturing & smart industry, among others. 

 

IoT is the fundamental element behind the global industrial transformation which includes Industry 4.0 and IIoT. The manufacturing industry is the leading IIoT market as majority of spending in IoT is centered around this vertical. The major use cases of IoT include manufacturing operations, production asset management & maintenance and field services. Following, manufacturing, logistics & transportation is the second largest segment from IoT spending perspective. These companies are looking for moving up their value chain using advanced communications & monitoring systems enabled by IoT. Freight monitoring is the major use case of IoT in transportation & logistics industry. 

IoT platforms form an integral part of the IoT architecture which connects the virtual and real world to enable communication, data & information flow, development of applications, among others, and provides analytics for connected devices. The different IoT platforms include connectivity platforms, data management platforms, Infrastructure as a Service (IaaS) or Cloud backend platforms, application enablement platforms and analytics platforms. The analytics platforms offer analytical tools such as machine learning, to extract valuable insights from IoT data. 

Nowadays, many companies are launching several analytics platforms on which enterprises can rely upon to get best in class analytics services. One such industrial IoT analytics platform was launched in June 2019, by Honeywell known as the “Honeywell Forge”.

Honeywell Forge previously known as Honeywell Connected Plant, is a reboot version of the “Sentience” platform which was launched by the company in 2017. Honeywell Forge is portable and extensible collection of enterprise performance management software, which provides actionable recommendations and highlights the economic impacts for business intelligence and business. The software uses process, asset digital twins and role-based & comprehensive analytics, which help in improving the decision-making process, resulting in improving the equipment performance, reliability, profitability and sustaining overall performance of the process and assets. Basically, this is an enterprise performance management cybersecurity platform with Software as a Service (SaaS)-based modules which enfold asset, process and control performance. The new Forge cybersecurity platform provides assessments to analyze operation technology systems, software to secure and configure infrastructure, appliances, monitoring and remote management applications and incident response processes.  

 

Within the industries, Honeywell Forge delivers role-based dashboards that display the digital twins of industrial processes by providing an extensive overview of the defined KPIs and their present operating performance. If any of the KPIs shows a slight deviation from the optima, the software starts giving recommendations on the best action that needs to be taken. Additionally, Honeywell Forge collects and integrates data from a manufacturer’s operations, analyzes it and then identifies the achievable optimal performance. Further, the IIoT platform augments the performance with predictive analytics to identify the scope for improvement. It then comes up with real time recommendations which helps the industries bridge the gaps and operate at peak performance. Honeywell Forge provides complete top to bottom visibility within the industry about how the operations division of the industry is performing with the help of its SaaS based offerings which are developed to meet the highest cybersecurity protections. Moreover, it helps the companies to overcome the pitfalls observed due to technology churn, aging equipment, shift in workforce demographics, among others.

 

Honeywell Forge unifies Honeywell’s process modelling experience with predictive machine learning analytics and produces digital twins which resemble the physical assets that companies can predict and then identify the major cause machine operation inefficiency and bring back the order to reliability and maintenance planning, process tuning and design change considerations.

Honeywell Forge is a customizable solution which can be tailored to fit in any kind of role as per the requirement within an organization. The Forge platform uses real time data to benchmark performance against best performance models to identify the opportunities. Using the enterprise view of the software, users can access the sites, units and identify the details around the opportunity with the help of process and asset information. Further, actionable recommendations can be used to resolve any kind of issues.

Honeywell Forge enables unification and organization of data (both process & asset) from various sources within a cybersecure cloud environment which can either be Honeywell’s cloud or the client’s cloud. From either of these clouds, using data analytics, the software detects the problems in machinery, identifies the root cause of the problem and aids prioritization of asset maintenance and corrective actions.

The Forge software is extremely scalable and accessible from anywhere in the world from unit, to site, to the extents of the organization’s enterprise. 

The advanced performance models contain predefined principles, models and templates for common plant process equipment such as pumps, compressors, among others. These models help in determining any kind of variation between the predicted and actual performances in real time.

Honeywell Forge enhances the traditional performance analysis using descriptive, predictive and prescriptive analytics. To forecast any kind of equipment failure, the data driven algorithms analyze the behaviour of a group of predefined parameters to estimate the time of failure.

The software supports both simple and most complex calculations along with simple mathematical operations and advanced functions such as regression analysis and standard deviation.

The FMEA and RCA logics detect the conditions contributing to degraded machine health or performance. These detection rules can be either statistical correlation changes or learned patterns or simple thresholds or predicted model-based deviations, among others.

The software itself compensates for any kind of missing or inaccurate or corrupt data. Similarly, the users have the flexibility to change rules or create their own cleansing routines.

The software ensures that the engineering units get automatically converted to suit engineering units in asset models.

This environment allows OEMs and others to develop content which will not be exposed and supports complex and specialized applications.

To meet the dynamic process monitoring needs, this feature allows for real-time execution of UniSim design models.

This is an extensive package of physical and transport properties, which enables high accuracy performance calculations.

This feature is used either to export data or reports or any other form of information to excel compatible files.

The data can be retrieved from various sources including DCS/ PLCs, excel, among others.

Asset model templates need to be created only once for each type of equipment. The asset-centric feature is supported by hiding underlying cryptic tag structures in typical DCS’s and historians. This eliminates the tag-by-tag configuration process for each piece of similar equipment. Additionally, it allows efficient change management on calculations and logic configurations.

This feature allows the users to detect the underlying issues using troubleshooting displays to find out the mistake in the logic. The users can also access the fault history, trends, graphic displays, among others using these tree & heat maps.

This feature allows the users to review and monitor all events (new & old). Additionally, the users can access the detailed event view for more information, launch event trends, among others.

This feature enables the users to update, review and investigate all the accepted events. 

The cybersecurity IIoT platform is available in three versions and allows the customers to scale whenever required to match their requirements and budget. The three versions are enterprise core, enterprise premium and site. The enterprise core version is exclusively for customers with more secure multi-site connectivity needs. This version delivers cybersecurity solutions by enabling secure data transfer with built in file threat detection feature. Additionally, it provides secure remote access with advanced granular controls designed for industrial environments. Enterprise premium delivers cybersecurity asset management solutions including asset discovery & inventory, continuous monitoring & alert generation, patching of software & antivirus management, risk & compliance management for actionable recommendations and mitigation of any issue or problem. Site version is entirely for customers looking for platform capabilities at a single site level and delivers all the cybersecurity solutions similar to the enterprise premium version.

 

Honeywell Forge works across industries on various monitoring applications and across a broad set of asset types including both mobile and fixed ones. Digital intelligence is the solution used by Honeywell Forge to combat the major challenges across various industries. Digital intelligence transforms the data into real time knowledge concerning equipment, process performance, health & energy consumption, among others. Honeywell Forge industrial solution is the backbone of real time asset performance management (APM) using unified data, analytics and visualization. With Honeywell Forge APM, the IIoT platform’s and the company’s data & knowledge are embedded into one business solution. The generated data feeds the digital twins, leading to real time KPI calculations and generation of on demand reports  and event notifications.  The integrated process & asset models help in identification of the bottlenecks, discover new levels of productivity and detect the potential threats. Here, machine learning and predictive analysis play an important role in delivering early insights in consideration to the potential machinery downtime and provide guidance in maintenance planning. This unified environment of KPIs generation and data establishes a common source of workflow between the engineering, maintenance and operations team. 

Honeywell Forge unveils the asset performance issues and guides companies to take recommended actions for reducing the asset related inefficiencies. Along with this, the IIoT platform continuously scrutinizes the operating and equipment conditions and identifies the performance gaps, if any. 

Effective asset management not only includes focusing on the asset conditions but also should look into how the assets performance is harmonizing with the process it is serving.

A combination of asset models and templates accurately quantifies the machine efficiency & performance and gives an indication about the machine health and the productivity of assets.

Honeywell’s predictive analytics machine learning models proficiently quantify the energy consumption and machine efficiency. The platforms data driven analytics excel in identifying early irregularities, reveal the root cause of any problem, provide estimates of future outcome, among others.

Engineers directly connect their algorithms with the continuously fed process-asset data. This saves both time and ensures effective asset management. Furthermore, the advanced configuration capabilities allow site experts to deploy OEM-provided machine models, execute advanced programming, run data science and data analysis tools from the APM database.

Based on the output of the performance, analytics and interactive calculation engines, Events notify the Events Dashboard, notify through email or by system alert.

There are numerous IIoT platforms available, globally, which are being used in different industries. Some of the IIoT platform providers include Amazon.com Inc., PTC, SAP SE, Hitachi, Siemens, Schneider Electric, Oracle Corporation, Microsoft Corporation, Cisco Systems Inc., Accenture, International Business Machines Corporation, among others.

According to TechSci Research, United States IoT in Manufacturing Market, By Component (Solutions, Platforms and Services), By Application Area (Predictive Maintenance, Business Process Optimization, Asset Tracking & Management, Logistics & Supply Chain Management, Real-Time Workforce Tracking & Management, Automation Control & Management and Emergency & Incident Management, & Business Communication), By Vertical Market (Energy & Utilities, Automotive, Food & Beverages, Aerospace & Defence, Chemicals & Materials, High-Tech Products, Healthcare and Others), By Company, By Region, Forecast & Opportunities, 2016-2026, the United States IoT manufacturing market size is predicted to register a steep growth in the forecast period, 2022-2026. The growth can be attributed to factors like increased digitization in the manufacturing industry and growing adoption of new and advanced technology like IIoT and Big Data. The rising adoption of next generation technologies and the need for predictive and proactive maintenance are the major factors driving the growth of the IoT platform industry. Based on the vertical, the energy and utilities segment is expected to lead the market due to applications like process optimization, plant automation etc. 

In another report by TechSci Research, United States Database Security Market, By Component (Software and Services), By Business Function (Marketing, Sales, Finance, Operations and Others), By Deployment Model (On-Premises and Cloud), By Vertical (Banking, Financial Services, & Insurance, Healthcare & Life Sciences, Telecommunications & IT, Government & Défense, Manufacturing and Others), By Company and By Geography, Forecast & Opportunities, 2026, the report highlights the development of the database security in the IoT market and how the market growth in influenced in the upcoming years. United States database security market is anticipated to show the robust growth in the forecast period on the account of large networking among many devices all connected to provide the advanced security against the rising instances of cybercrimes. With leaks in the personal data, hacked security inferences in the authoritative organizations and much more dangerous threat, the demand for the perfect solutions against the risks is anticipated to drive the market growth in the future. In the year 2020, the world experienced an out break of COVID-19 and the businesses expanded over the online platform. With businesses growing online, the questions of the database security is raised and thereby the demand, thus supporting the growth of the United States database security market in the upcoming five years.