Is IIoT technology revolutionary for Manufacturers? Is it actually good? Why is it of interest? - Part 3 [END]

In previous parts, I compared the Industrial IoT to the Traditional system when utilizing the manufacturing data. We discussed 'Stage 1 - Detect & Monitor' and 'Stage 2- Collect & Store' in Part 1 and Part 2 of the article.

Stage 3 - Analyze & Report

In Part 3, we will talk about the stage of Analysing and Reporting the data. What type of applications we can use when choosing between an IIoT and a Traditional system.

6 Type of Applications & Method used for Analysing and Reporting data

1. Manually Create Reports
2. On-Premise Custom application (Traditional System)
3. On-Premise Application (Traditional System)
4. SaaS Application (IIoT system)
5. Custom SaaS Applications powered by a cloud platform (IIoT system)
6. Business Intelligence Tools

1 Manually Create Reports

When there is an initiative to use the manufacturing data (such as cost-saving), this is the first approach a manufacturer usually takes and is the industry's most common approach. Querying the sequel database or downloading a CSV file from devices for data and analysing the data through Excel to create the reports.

Pro:

• Quick and flexible
• The go-to method to finding a quick answer.

Con:

• Time-consuming and
• Required an experienced person to perform
• Prone to human error

2 On-Premise Custom application (Traditional System)

The system created locally by a niche vendor is relatively cheap and can be highly customized to match your requirement. The issues are that these systems do not really conform to standards or benchmarks and do not have any certification to guarantee it's quality.

You will also have to rely on the particular vendor in the future, and the quality of the software directly depends on the quality of the vendor's developer.

Pro:

• Usually cheap
• It can be highly customized

Con:

• Vendor tie-in
• Uncertain quality

3 On-Premise Application (Traditional System)

These are the best in class applications developed by multinational companies. For example, just for the SCADA systems, there are AVEVA from Schneider Electric (formally Wonderware), Ignition from Inductive Automation, WinCC from SIEMENS, etc.

For every type of system, there will be applications from leading companies to meet your requirement. Choosing between them is choosing between the features available and somewhat personal preference.

This type of application will have many use cases and customer references, be proven quality, feature-rich, and highly regarded. They will also come with a hefty price tag since you are buying quality outright.

Pro:

• Best-in-class
• Large user base and customer references
• High quality and feature-rich

Con:

• Expensive
• Large initial investment

4 SaaS Application (IIoT system)

SaaS (Software as a Service) applications for industrial applications are relatively new. SaaS applications have replaced the on-premise applications in many segments, notably the ERP (Enterprise Resource Planning) segment, where SaaS solutions have become the dominant type in the market.

Characterised by their small initial investment, powerful system, hassle-free maintenance, and highly scalable solution, SaaS solutions have become the go-to system for many software segments.

SaaS solutions have to be used with an Industrial IoT system and not the traditional system. Although hybrid systems exist from the on-premise system, they are less like a SaaS system than the On-Premise system.

Credit: Ignition by Inductive Automation

Examples of SaaS IIoT systems are SIEMENS Mindsphere, PTC Thing Worx, Schneider Electric EcoStruxure.

Pros:

• Small initial investment
• Best-in-class Powerful system
• Hassle-free maintenance
• Highly scalable solution

Con:

• Require internet and additional network security
• Not suitable for an organisation that has a policy that does not allow for cloud connection.

5 Custom SaaS Applications powered by a cloud platform (IIoT system)

This is a very new and up and coming category of software powered by the Cloud IoT. AWS (Amazon Web Services), the IoT services are; AWS IoT core - MQTT broker and more, AWS Sitewise for Industrial modelling, AWS IoT Analystics, and AWS Greengrass - software for edge devices. I am more familiar with AWS services, but other clouds such as Azure and Hawaii do offer similar services.

Vendors can utilize cloud IoT services to build a state of the art application and offer them as a SaaS solution to the manufacturers. These Custom SaaS applications are of higher quality than the On-Premise Custom Application since they are based on high-performance serverless services that are highly available and scalable.

Vendors can also get their system certified by the cloud provider to further guaranteed their system. 'Appomax Energy Management' - our SaaS application for Energy Management is 'Powered by AWS'. To get the software certified, we had to join the AWS partner network and get our architecture certified by AWS.

Pro:

• Small initial investment (just like other SaaS applications)
• Cheaper than off the shelf SaaS IoT application
• Best-in-class Powerful system
• Hassle-free maintenance
• Highly scalable solution

Con:

• Application quality depends on the certification
• Require internet and additional network security
• Not suitable for an organisation that has a policy that does not allow for cloud connection.

6 Business Intelligence Tools

BI (Business Intelligence) Tools are a sophisticated tool, but they require a BI specialist to set up the dataset to use the data. BI tools enable end-user to repeatably generate reports quickly and accurately while allowing the freedom to analyse the data.

The cost of the BI tools such as Tableau, Power BI (Microsoft), and Google Data Studio has come down a great deal, especially now that SaaS pay as you go licenses are available. Manufacturers do not have to purchase the tool outright.

The limitation of the BI tool is that it is exclusively an analysis and reporting system. On its own, it does not allow any input of contextual data. Information such as the manufacturing plan or the reasons for the machine downtime, if not already collected, cannot be added directly.

Because of this limitation, the BI tool, although powerful, should be used as an add-on for the traditional or IIoT system instead of a stand-alone system in the first place.

Pro:

• Powerful for analytics
• Flexible

Con:

• Require a specialist to setup
• Cannot input data

Application type comparison table - Traditional vs IIoT

Conclusion - Traditional vs IIoT system

So... "Which system should you choose?"

The answer is as always... "It depends"

I will give you a clearer answer. I would say the two biggest factors are

1. The size of your organisation
2. Whether you are installing a new system, adding a system or replacing the existing system.

Manufacturer Size

• Small - Revenue <500M THB (<15M USD)
• Medium - Revenue 500M-2,000M THB (15-61M USD)
• Large - Revenue >2,000M THB (> 61M THB)

Industrial IoT systems tend to be of a better choice as we advance as they are cheaper, faster, and better than traditional systems in most cases, with a few exceptions. For the large manufacturer, the cost and time to implement IIoT and Traditional systems do not differ much. The large manufacturer may benefit more from the traditional system as they have more control and customization.

Small and Medium manufacturers, on the other hand, benefit more from an IIoT system. This is especially true if installing a new system as the IIoT technology tends to be cheaper, requires lower initial investment, and has better features than the Traditional System.

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To read the previous parts

• Link to Part 1
• Link to Part 2