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The post How to Populate Oracle eAM Meters and Quality Plans Automatically first appeared on STR Software.

The post How to Automatically Load Data into Oracle Process Manufacturing first appeared on STR Software.

1. Including collection plans with meter reading requests in your work orders. Frequently, collection of this data is ignored as your maintenance workers are strapped for time and under pressure to move on to the next job. If the data is collected, then someone on your team has the tedious job of manually entering the data into eAM.
2. Heavily involving IT to write, maintain, and troubleshoot custom programs that import each controller’s proprietary data file into meter readings or collection plans

Scenario one is a very manual, multi-step process that often results in errors from transposed numbers or illegible handwriting. Scenario two places a heavy burden on IT not only to create but also maintain these custom programs to continuously push data into Oracle eAM. Many organizations entirely abandon the idea of using asset data to optimize maintenance because IT departments are already stretched thin and manual data collection is time-consuming and deprioritized.

Instead, the next best practice is to maintain assets on time-based estimations rather than actual usage. While this practice ensures regular contact with your asset, it can result in over- or under-maintaining of the asset which contributes to unpredictable maintenance costs, unanticipated equipment failure and unproductive maintenance teams.

DataVaya from STR Software solves these problems by automatically collecting asset data from your machine controllers, sensors and historians then imports it into Oracle eAM. This data can be used to populate meters and kick off preventive maintenance work requests if the meter exceeds a threshold.

In addition, data collected with DataVaya can populate collection plans for data analysis, giving you visibility into asset operating health. With DataVaya, not only can you determine exactly when your asset has hit 2,000 hours of use and have a preventive work order automatically kicked off, but you can also collect heat sensor or vibration data over time to learn the condition levels that indicate your asset needs maintenance.

The automated collection of asset data through DataVaya offers significant savings for your maintenance program. One of our customers determined that by eliminating the manual collection and entry of asset data, they save about $1000 in labor costs per asset each year. In addition, this customer now has a consistent flow of accurate data into eAM so they can create work orders based on data – not time.

In summary, DataVaya is an automated solution that integrates seamlessly with Oracle eAM to collect data from machines and deliver it to Oracle eAM. By making your asset data available to Oracle, your maintenance organization can harness eAM’s powerful workflow functionality. DataVaya bridges the gap between your assets and eAM so you get the most out of your investment in the eAM solution and extend the life of your assets.

To learn more about automatically delivering machine data to Oracle eAM with DataVaya, contact us here.

The post Automating the Collection of Machine Data into Oracle eAM first appeared on STR Software.

There are four distinct modern advancements at the foundation of why IoT is here now and is going to stay.

1) Sensor cost:  Over the last couple of years sensor costs have rapidly declined. What used to cost thousands of dollars per sensor is now available for less than a $100 and comes with its own operating system, sensors and Wi-Fi radio.

2) Affordable broadband internet availability and Wi-Fi connectively:  Wi-Fi is everywhere and broadband internet connects are inexpensive. From our homes to remote oil fields, we are able to connect our phones, tablets, laptops and now sensors and control panels that monitor and control our most important assets.

3) Processing Power and the Cloud:  The evolution of computing power shows no signs of slowing anytime soon. Combined with the cloud, we have supercomputers available to us at a moment’s notice to accept volumes of data, processes it, perform complicated and resource-intensive analytics providing us answers in minutes, and sometimes seconds.

4) Mobility:  Miniaturized computers in our pockets, purses or briefcases allow us an unparalleled level of convenience for accessing data at a moment’s notice.

Each advancement in its own right is so valuable to our modern lifestyle that it more than stands on its own. But in order to deliver on the lofty IoT promise, each advancement must be represented equally for businesses to truly realize business value.

The post Why is IoT Popular Right Now? first appeared on STR Software.

Big data analytics can be a standalone solution or built into integrated solutions. Regardless of how it is deployed, big data analytics allows businesses to take in very high volumes of data, at high rates of speed, from numerous sources and make informed decisions to optimize how an organization operates.

How does Big Data Analytics relate to Internet of Things (IoT) and Industrial Internet of Things (IIoT)?

The evolution of big data analytics is going to be critical in the ability for Internet of Things (IoT) to provide the measurable value promised to organizations. Gartner has issued a conservative estimate that by year 2020, connected devices will grow to 26 billion units.

Each one of these 26 billion devices monitoring business operations will generate thousands of data points each minute, hour or day. Big data creates a dizzying amount of data to sift through, analyze and report on.

With the true value in IoT being the connection between devices, datasets grow exponentially very quickly. It then falls on big data analytics to help humans determine as close to real-time as possible where we should focus our attention to meet business objectives.

By the way, prominent technology organizations believe Gartner’s estimates are extremely low:

The post What is Big Data Analytics? first appeared on STR Software.

Having been around for years, an M2M solution typically means that the data collected is delivered to a dedicated software application. Its goal is to monitor, troubleshoot, and diagnose operating performance and issues with machines, assets, or other types of devices.

M2M is -> point-to-point -> vertical -> closed -> requires commitment **

This is different than the newer IoT mindset where large volumes of data points are collected across a broad range of devices (“things”) and integrated with big data analytics in order to optimize the supply chain, streamline manufacturing, and/or improve overall asset health through predictive, conditional-based maintenance.

IoT is -> multipoint -> horizontal -> open -> allows experimentation **

** Source: ABI Research © 2014

The post What is the difference between M2M and IIoT? first appeared on STR Software.

IIoT is software and hardware (connected industrial electronics, sensors, meters, etc.) working together to collect, analyze and trigger a response in an industrial environment. Responses can be in reaction to a point-in-time event (machine breakdown, min/max thresholds exceeded, etc.) or a response can also be triggered before an event occurs by using predictive data. By using data collected from sensors or meters over time, related software is used to determine trends and predict the likelihood of an event occurring in a given amount of time.

IIoT is also commonly referred to as M2M (machine-to-machine), although in many cases unfairly.

What is an example of Industrial Internet of Things (IIoT)?

Consider an industrial environment (a manufacturing plant or a mine) having heavy equipment run by engines. In order to keep operations running smoothly, management typically has teams of maintenance professionals on site to ensure high levels of equipment or asset reliability. Maintenance workers may take meter readings daily and report on the number of operational hours each engine has run. With this data, they can plan for scheduled downtime to perform routine maintenance and prevent unexpected equipment breakdowns.

While this is all helpful, the gathering of the data is inefficient. IIoT can automate the process of collecting basic data and expand the number of variables collected including things like fuel consumption, load, exhaust temperatures, external temperature and air quality. This data is then passed to software to quickly analyze and visualize asset performance in real time.

The result is that you now have access to the mechanisms and tools required to consume and visualize vast amounts data in a way that allows you to materially impact the performance of your organization by predicting failures before they happen.

The post What is Industrial Internet of Things (IIoT)? first appeared on STR Software.

To start, let’s describe “things.” A “thing” is any physical object embedded with electronics (including sensors and software) that are connected (or can communicate) with another “thing” over the internet. As soon as one “thing” communicates with another “thing” it becomes “things.” And there you have Internet of Things (IoT). Need an example?  Keep reading!

What’s an example of Internet of Things?

One of easiest examples of a “thing” to understand is a consumer-based smart thermostat. Traditionally, thermostats were designed to regulate temperature in your home based on a high or low temperature threshold (depending on the time of the year). Through IoT, a smart thermostat can regulate temperature using data from various sensors located in your house. These sensors may measure humidity and motion or sound inside the home.

With motion and sound detectors connected to your smart thermostat, the smart thermostat knows when you are home and sets the temperature according to your preference. Once you leave for the day, the thermostat adjusts the target temperature to a more energy efficient setting saving you money and the environment at the same time. Also, by measuring humidity, it can engage a humidifier or dehumidifier as needed keeping your home as comfortable and efficient as possible.

In addition, smart thermostats may connect to your home’s wireless network so they can gather data about outside weather conditions from the internet including hi and low temperatures, precipitation, humidity, barometric pressure, etc. Why capture of this this information? Well, with it, the smart thermostat can forecast temperature changes during the day and make intelligent decisions about heating (or not heating) an empty home knowing that outside temperature will naturally heat the home to the desired temperature.

This IoT technology makes a significant difference in energy efficiency. By interfacing your smart thermostat with sensors and external data, you can lower utility bills by up to 20% annually.

This is a simple example of smart thermostat functionality and only touches on some basic functionality. Built-in artificial intelligence (AI) is also available and is designed to learn about your daily activities/schedule so the thermostat can operate autonomously without human interaction. The thermostat may also be activated by receiving information from your smart phone. If you indicate that you are on your way home, the phone can quietly alert a smart thermostat to your upcoming arrival and set the system to hit your preferred temperature by the time you walk in the door.

The result is household temperatures customized to your preference, 20% savings on your annual utility bill, and a cleaner environment for all of us. By the way, like most “things,” humans have the ability to override the system to cool or heat on demand.

Now that you understand a consumer-based example of IoT, check out IIoT.

The post What is Internet of Things (IoT)? first appeared on STR Software.