Data Management Significance in IOT of Manufacturing Industry

In the previous blog, we discussed IOT (Internet of Things) impact to consumers and challenges in data management. This blog focus on the various industries impact of IOT and how it is revolutionizing them. Later we also discuss the importance of applying the data management principles for improving the outcomes.

Consumer IOT made the significant impact by providing valuable services to customers with many smart devices makes life easy for the users. But commercial usage of IOT adaptation might be slow but there is a potential to disrupt and revolutionize the industries and solve many of the business challenges they never had solutions in the past. As shown in the visual of ice burg the Industrial/commercial IOT   is very large with many solutions like smart sensors, smart buildings, smart factories, digital supply chains.

Industry 4.0

 The world of manufacturing is going thru major disruption and revolutions which is called as  Fourth Industry revolution.

 First industry revolution which happened till the eighteenth century where availability of steam and water. Availability of steam provided the first mechanization of the world. Hand production methods moved towards to machines. Textile production improved productivity, steam machines provided better transportation . Second industry revolution started in the early nineteenth century with innovation and adaptation of electricity and improvement of the manufacturing process of assembly lines. This revolution moved towards mass production of goods. Availability of transportation facilities to provide these goods  to sell across the country or even world.  The assembly lines process managed might be a paper-based process but still efficiently deliver product in mass scales like hundreds of cars in a month or thousands of soup cans. The mass production process even went in the agricultural process of invention of better seeds by GMO, drift irrigation, supply chain to reach product in the market intern able to reach all kinds of foods on everybody's kitchen tables.

After the invention of the computer and software started third industrial revolution improved the industrial engineering to next phase of improvements. Moving paper based process into computer applications, automation of process all improved overall performance which improved output. Automation of the production, which improved productions worldwide and made mass production more efficient. Now the world of manufacturing going thru next revolution. The fourth industrial revolution, also termed Industry 4.0, is being characterized as an increasing digitization and interconnection of value chains and business models. Industry 4.0 creates Smart Factories and is based upon cyber-physical systems allowing the manufacturer to control the entire production from one platform.   Industry 4.0 involved achieving total connectivity with IOT (Internet of things) which also called industry internet.  Industry 4.0 makes the existing manufacturing applications increase the complexities in very significant level which involving adapting new machinery or changes to existing physical systems. With the emergence of big data platforms where they can collect the massive amount of data and as well as intelligent devices which can collect and send a large amount of data paired together comes with the new generation of software applications which are a lot more intelligent with least amount of human interference.

In short, whether it is a jet engine, turbine, commercial conveyor belts when connected with smart sensors sends data in real time can help to track, optimize, predict what to repair, when to repair and even when to replace. This will change how manufacturing industries operate be supporting their large and expensive machines. For example, GE who is known to build large Jet Engines, Turbines are looking to digitize their operations to improve their productivity as well as their customers.  Also Electrical engines in cars with many smart sensors taking cars close to driver-less cars.

Smarter Devices /Machines

 Many existing Machines are integrated with external IOT devices which collect a lot of information and send to central IOT application. A smart Nest thermostat will help to operate the HVAC systems more efficiently and also collect information about Air conditioner performance. Next level of HVAC systems is coming with inbuilt IOT chip which can help to operate the system, collect health data, diagnosis and selfheal the systems.  New generation turbine has built in 200 plus sensors collect a large amount of data helps to operate more efficiently and manage its maintenance schedule.

 Whether it is Industry distribution network or Factor Floor there will be a lot of smart sensors gathering a large amount of information and alerts any changes significantly impact the outcome, many of these devices can be operated over the internet thru an IPAD, kiosk or Laptop. With all the real-time information and instructions efficiently processed could improve processing efficiency very significantly also reduce human interaction or manual work.

Many times in factory floor some of the machines are critical for the production process and if any breakdown will stop the production. When machines break down technicians want to fix the machine with very limited data and spend a lot of time troubleshooting to find the root cause. Due to the criticality of the machine sometimes these are replaced even they are operating in good condition because there is no way they know when it is time to replace. Machine replacement cycle is based on the usage duration not the status of the machine at the current state. But the smart machines will constantly send health diagnostics and performance data which could help to easily identify the problems with the machinery. Also with all the information from IOT machines can gather health information and could even heal very trivial problems without a technical get involved.

Smart Meters

Utility companies had the major technological revolution by introducing smart meters which can collect the usage data and send to the Local utility company in very real time.This information can help to optimize the distribution of utilities and also evolve incentives to change the usage patterns. The real-time energy usage data can help to identify fallouts, energy loss etc.. This gives the tremendous ability for the utility company to have more accurate energy forecast, efficient distribution. The next level of revolution could be capturing data of various circuit breakers to identify inefficient appliances and suggest customer on replacing them.  The smart utilities, smart sensors, smart devices could lead to smart buildings which have higher energy efficiency and comfortable environment for the customers. Also, management of facilities is a lot more efficient with smarter devices around over the Internet/Intranet.

Smart Factories

Automated process control, real-time production monitoring, real-time integrated manufacturing and environmental conditioning/monitoring are made possible because of IOT devices adoption, the platform for able to consume a large amount of data and analyze ( Big data platform).  Part of industry 3.0 moved many manual processes into computer applications but still managed by Factory operators and quality control also manual process in some cases. All of these are slowly moving to automation of business process with many health and quality information from the machines collected, analyzed and decisions are made in control centers.  Smarter logistics, smarter Machines/Robots, smart grids, smart buildings, smart sensors and smarter controls (Kiosks, control center, mobile applications) are making factories optimizing and improving productivity least amount of labor costs. In short smart factories, revolution is fueled by IOT devices and large data platforms.

Similarly, supply chains are optimizing with total connectivity between suppliers, warehouse, Factory (Production), distributors, consumers with real-time information. This helps to move forecasting model to close to real time demand model, real-time inventory management, accurate logistics and overall revolutionize the manufacturing and retail industries.

Now let’s discuss about “Data Management”

With the industrial revolutions brings the new set of software applications and a large amount of data/information.  These applications are very different than conventional enterprise applications we are building from last three decades. These applications connect with devices in real time and gather information in very real time at times many gigabytes of data for every hour. Most of these applications have high scalability, high availability, demanding and critical business needs. When hundreds of these devices communicate in very real-time required sub-second response times and at times in the range of thousands of Transactions of seconds. Also, devices could be set up in the very large geographical area so that forces to keep these IOT applications running in cloud-based infrastructure (sometimes it could be even on a private cloud).

The cloud-based IOT applications also need to still connect with existing enterprise applications (ERP, CRM, sales/marketing, customer service, etc...) and exchange data so the IOT application operates to fulfill the customer needs. In last thirty years, the enterprise application collected lots of data in application and current data management methodology segregates this data into two groups, Master data, and Transactional data.  Master data tells who is the customer, where is the location and what is the product. Transaction data will be all the operations using customer data like customer purchases, customer support requests, customer browsing history and much more.  In this environment, Transactional data is typically 100 times of master data but still, master data is critical to better understand and analyze Transactions for better business decisions.

If you look at below diagram wherein current data ecosystem without IOT devices where current enterprise applications focus on master and transactional data, but device usage data never captured by the application as all those are the manual and user-driven process.  The usage data if they collected could be the larger volume than transactional data. The usage data might have lot more critical information to help enterprise operate efficiently, improve the device to perform better. Before IOT  there is no easy way to collect the usage data and the industry 4.0 enabled to collect usage data and also automate the device usage.

                             Data organization Before IOT

                                         Data organization with IOT

As you could see in the diagram of "Data Management with IOT devices" where IOT applications are collecting the usage data will change the data management paradigm. The usage data still need to connect with Transactional data and master data to give the complete context of the information. The IOT device data still need to understand the customer, location, and device.

Even smart devices will be maturing on both hardware and software design and implementation. We all heard of multiple generations of the same device and sometimes even have subversions of the hardware of the same device in the usage. Similarly, there are multiple versions of firmware exist which is communicating to the central IOT Cloud application.  To understand the interactions between the device goods to, it is very important to know the right hardware and software versions the device running. Next Similarly we need to know where the device operating accurately, also who is the customer and users of the device. The device could change locations or change the users/customers.

All these lead to the importance of Master data and managing it with MDM methodology and then integrate the MDM data with Transactional and usage data. So it is important to understand the intersection between these different elements of data and plan enterprise echo system where all of these can co-exist.

When an enterprise already invested in Enterprise operational systems like SAP ERP, CRM and many other sales, marketing, customer service systems it is important to integrate with the cloud applications and also their corresponding analytical platforms. Every new sale, operational systems need to connect back to IOT applications. For example, when a device gets registered first times, the device customer/user get identified and connected to Enterprise customer master. Same time location information also tied with the Device and customer. Whenever customer/location changes they need to be updated in both IOT application and enterprise applications. Enterprise applications provide support and IOT Cloud applications should have consistent customer information related to the device.

 In manufacturing plants, the devices could be a machine in the product plant represented in ERP systems and the Information from the device need to reflected into ERP systems so an enterprise can take advantage of up to date latest information from the devices.

Data Management in IOT (Home Automation)

We all hear Internet of Thing and Big Data is big words we hear as new big trends which could change the future of computing and will bring next technical revolution. This Blog is focusing on discussing the IOT in home automation and its impacts. We also discuss how data management is changing with IOT.

IOT in Home Automation

IOT is maturing slowly despite the push from big fortune 500 companies. If you look at smartphone revolution of last 15 years, I would say we are in first the few years of that adaptation curve.  If you look back to years 2003 to 2005 smartphones are predominantly used to check emails or browse the internet at the slowest speed. For many people, it is the luxury item in those days where the smartphone is very necessary within 15 years’ time.  The change is so phenomenal that we could practically operate our bank accounts, purchase Tickets, interact on a social network with friends on another half of the earth or have fun by playing candy crush or watch your favorite football game live anywhere sitting in the world.

Now coming back to home automation we are in that early days of a smartphone revolution. There are home automation tools that can be operated from your smartphone. You could automate (in US market) your central Air conditioner/heat, garage doors, sprinkler system, security camera’s, security sensors, Fans/lights, front door locks and much more. Many of these have very practical uses for more comfortable life and building a smart home. But at the same time, people are cautious of the aspect of privacy (Some big guy is watching you) or these could lead to additional security threats. For example, tools like “Sesame” could be used to open your front door without using a key from your smartphone anywhere in the world. There could be practical uses at times where you are stuck in traffic and your kid (or well-known guests) is waiting at the front door.  But what happens when a thief is able to hack it? Take an example of Tile, where it helps you track things like wallets, car keys and pets. Tile could be a useful tool but could easily be used to track people and loose their privacy. All they need to do is to leave the tile in your car to track where you’re driving or leave it in your laptop bag to track where you currently are. So does privacy trump convenience?

Things like Amazon “ECHO” or Google “Home” are more like “toys” for people but could evolve central consoles in the future to manage all IOT devices. At the same time, it is very hard to replace the smartphone in people’s hand with these devices. In short, there is a lot of opportunities for a company like Apple to revolutionize IOT.

A few of the IOT devices that are commonly used are:

    1. A Smart Thermostat (NEST) can be controlled by smartphones and self-learning features that can reduce the energy cost.  The new versions of Nest can be controlled thru Amazon “Echo”

    2. Smart Sprinklers controller (Rachio) which is the replacement of a manual sprinkler controller and gives an additional functionality of managing all the functionality thru iPhone and with the additional intelligence of integrating to weather reports.They promise the intelligent management based on soil type and weather conditions. The latest versions can be controlled thru devices like Amazon”Echo” or google “Home”.

3.what If your car can tell what’s wrong with it?. If there is a smart device can communicate with the Car owner about the condition of Car?. There are many devices in the market “FIXD”  is one of those used the diagnostic tool connect to redirect the information to your smartphone. 

4.Smart Garage Door Opener (MYQ) which helps to control your garage doors thru smartphone and thru internet..

5.    Front Door Opener (SESAME)  is the smart lock is an add-on to existing locks/deadbolts of your home controlled thru smartphone and can open the door without keys and also lock and unlock the home over the internet.

6.    Remind the important things (Tile) again an application can warn you important things like Wallet and also helps to locate them where you left them lost time and also find the lost things.

7.    Home security Camera (Ring):  there are many applications where you could see if somebody knock your door before you open the door. You can see them on your smartphone and communicate with them too.

There are lot more of similar devices and they keep evolving to specific needs Probably adaptability and price is barriers as well as security and Privacy. But in our distance future our dishwasher, refrigerator can alert us on our smartphone or Alexa (Amazon Echo) when there is a problem.  Same time are we ready to pay additional $300 for an appliance for this feature.  One of the major concern for consumers will be about somebody could take advantage of the information. For example, if somebody can hack “sesame” and open the front door without a key could risk the family. Many of these hiccups will be fixed in future and confidence on these devices to grow.

This is just illustration of how Data Management happens in IOT

Now look at Data management aspects of IOT:

Most of the IOT devices interact with the central cloud application and sends a lot of data as well as user interactions thru the smartphone application. Most of this data is very helpful for the consumer to measure the usefulness of the device as well as Device manufacturer to improve the device. But the data gathered thru the process could be enormous value for communities if used for positive causes. The data could be enormous as over the course of a year a device could be sending many gigabytes and collectively could lead to trillions of records.

Is this unstructured big data?

It all depends on how you look at it. Most of the data going thru interactions are very structured with specific information and instructions like” switch on my Air conditioner”.  But same time, if you use a relational database as backend for operational management, could be possible depend on volume but could get into scalability challenges pretty quickly.    ACID (Atomicity, Consistency, Isolation and Durability) principles force you to either accept higher response time or look for alternative solutions in big data stack. But same time high availability, reliability and quick response time are the challenges need to work thru as still need to be considered. Solutions like Mongo DB or Casandra could be alternatives.

But the data collected thru these interactions and organized properly could provide a lot of insights for consumers, device manufacturer as they could provide valuable information provider as the additional source of business or even helping the community.

Let say example like smart Thermostat can provide insights into his energy usage based on the number of hours the Air-conditioner operating/Heater operating which could help to manage costs and improve efficiency. If this data collected over the years can also provide impacts on seasonal changes and alert conditions like insulation wareoff or malfunctioning of appliance etc.  Similarly, if usage records of all devices within a city can give you greater insights like weather impacts, the condition of houses, energy demands and what not. Again if privacy is not a concern there are tons of air-conditioner companies would like to access this data to sell new one if they know the customer is looking to replace soon based on the information. So the data is very useful if we put statistical and predictive analytics on top of this data to get answers to a lot of unknown with significant confidence (not necessarily 100% but mmaybe70% ). Given the high volumes of data an EDW might not a right fit and push for data lake and big data as an option but the results of insights still need to be structured to articulate in a very meaningful way, that could results still having a conventional BI solutions.

How MDM fits in?

Master data management has a very critical role in the solution despite hypothetically the user has only one system of record (that could change the scenarios like using devices like Amazon “Echo” to control).

Taking same smart Thermostat example, when user register himself and his device(s) is the first origination of master data and should be simple as there is a single source of entry.  It should be static and should be decent quality, is not it?. Not so fast. Let's look at some of the scenarios

If the facility is a rental home or vacation home. You add devices for few weeks to few months and then the devices move to a new owner, so the device movement between users could be challenging thing to manage.

What about many life changing events like marriage, divorce, move out of the home all these could have an impact on the underlying data and need to be managed properly in master data?

As well as when a device is retired and replaced with a new one the continuity of the new device statistical data connected to the old device is also critical to have the connectivity of statistical information. Most of the electronic devices are outdated in few years or becomes faulty and need replacement in few years the device mastering is very critical too.

So Both Devices and Users need to be mastered with MDM principles and best practices for improved quality of service to customers as well as to keep accuracy of analytical data.