Market trends for Industry 4.0
As we already saw glimpses of IoT market trends, let us now have a overview of what Industry 4.0 holds for 2017.
- Manufacturing
It is going to be surprising for people who think rapidly changing, customer-specific mass production is a dream for future to accomplish. Industry 4.0 manufacturing architecture which is fast, customized and automated is soon expected to become a reality. It seems futuristic fantasy but we will soon see some amazing implementations of it. It will take time for the industries that are mass production centralized and sophisticated. But some new, small and decentralized organizations units are expected to see the ray of light to meet customized individual needs.
- IIoT Platforms
IIoT platforms are blooming almost everywhere. Organizations are integrating data hubs fir storage, processing and analyzing the data. It is a wild growth phase which is sure to persist for next two years. We will also witness increasing demand of device integration, data management, device management like software updates and also business process management. IIoT applicants are also looking for easy-to -use connectors which are fast and simple to deploy.
- Industry 4.0 data integration
We live in a diversified world and it will remain this way in the future. In IoT, elements like big data, machine learning and analytics play a big role. But the issue is to combine the diversified data that is created by each individual in a meaningful way. IoT elements needs to utilized to its optimum utilization power to do so.
- Users become Industry 4.0 vendors
In near future, we will witness typical enterprise users who have experience of IoT or Industry 4.0 trying to market their knowledge and expertise to external customers. This is how enterprise users are entering in the Industry 4.0 and IIoT market. They offer their own technological developments and may even offer consulting and integration services.
- IoT Ecosystems
In current scenario, where economy is highly interconnected, the strength of network plays a vital role rather than the size of company to determine the revenues. This particular concept is critical in Industry 4.0. Iot Ecosystem is expanding frequently and will soon provide complimentary micro services. Increasing number of partners are attracted when there is a strong business model and core solutions which depends on the maintenance of network. An intense competition will soon emerge between top notch IoT ecosystems. All these will have great impact on industries too which will help Industry 4.0 to a greater extent.
Layers of Industry 4.0
Layers in any industry depict the substance and core of everything that holds it. Let us have a quick look at what Industry 4.0 is integrated of:
Technology Integration
Technology Integration helps to facilitate physical-to-digital transformation. It connects certain hardware components, applications, supporting systems, etc to the equipments and plants in different locations to share data management and analytics.
Data Management
Industries store their data in different systems. Whether it is financial, sales, marketing, operations, production, manufacturing -all belong to a different system storage. The Industry 4.0 can be put to utmost use for combining these data for holistic view of the business. A component of the data management layer called ‘data lake’ is used to combine all such data from multiple sources on a cloud-based warehouse that can be useful for real time analysis and decision making.
Advanced Analysis
Industry 4.0 helps to collect, aggregate, store and process data. This associated data can prove to be game changing for companies to drive analysis and conclusions. Data regarding processes, supply chain, energy usage, etc can be fetched to draw meaningful insights. But all these useful only for the talented and experienced analyst.
Digital Interface
The digital interface is a critical layer. This is the step where all the results and conclusions derived from analysis of the collected data is delivered to the business user. Reports are conveyed in a useful and meaningful way so as the delegates can plan the future steps as well as understand the market and industry better.
Thus, we can see that Industry 4.0 is no longer a future in any industry as it is becoming a core part of the happenings and operations of organizations.
Introduction to OEE
Overall Equipment Effectiveness (OEE) is a standard that measures the percentage of manufacturing time that is truly productive. It helps to measure manufacturing and production productivity. OEE supports TPM by carefully tracing the progress and downtimes to achieve the determined target of perfection.
An OEE score of 100% depicts production excellence.- An OEE score of 85% depicts ‘almost’ perfect for manufacturers
- An OEE score of 60% depicts typically fair chance for discrete manufacturers
- An OEE score of 40% usually depicts lack of TPM
OEE takes into account the following components that maps with the TPM goals and considers different types of productivity loss.
- Availability
Goal: Zero Stoppages
What it does? Availability Loss are taken into account that includes events that delay or stop the planned production for a noticeable amount of time. Events like breakdowns (unplanned stops) or changeovers (planned stops) fall in this phase.
- Performance
Goal: Restrain short stops or Slow cycles
What it does? Performance Loss are taken into consideration that scrutinize the factors that cause machines to operate at less speed than the expected speed when running fall in this phase.
- Quality
Goal: Zero Defects
What it does? Quality Loss are taken into consideration that look for defects are areas that require rework. Event like Production Rejection is an example of this component.
- OEE
Goal: Seamless Production
What it does? All the above losses ( Availability, Performance, Quality) are accounted which helps to measure true productive manufacturing time.
To compute the productivity losses, measuring OEE is extremely important so as to measure and trace improvements.
IIoT and Machine tools
Machine tools will soon be referred as cyber physical systems (CPS). CPS regularly pops up in the IIoT discussions. CPS can be defined as an architecture where embedded and networked computers monitor and control the physical processes with a feedback loop.
Flexible machining environment where machine tools are equipped with in-process measurement and closed-looping structures are helpful for IIoT integration. Compressed air lines, hydraulic systems, chip conveyors can all be part of this integration marathon.
One of the crucial application that requires cyber physical systems is the energy management in factories. It requires to monitor and manage the power consumption by each device, machine and other equipment. This development can optimize the energy consumption and balance the speed. This way machine operations that are energy intensive can be scheduled during the day when utility rates are minimum.
Currently, the important and useful concept regarding cyber physical systems is control loop. Industrial IoT can help to implement the control loops from device level to the enterprise level in factories.
Stepping on the IIoT Pathway
A monitoring software is an application that talks to numerous devices and provides real-time dashboard to the industries which is notification and reports driven to improve the productivity and prediction ability and is one of the integral part of IIoT
Machine shops are now stepping in to utilize the strength of Industrial IoT. Most of them are installing the monitoring system. This is the recommended approach as machine monitoring can introduce the main elements required for IIoT connections. Basic machine monitoring requires equipping machines, establishing the framework for data collection and network configurations, training supervisors and managers to deal and recognize the data management issues, and the list goes on.
Most of the shops that implement monitoring system tend to implement these in modules, with a small number of machines so as to ease the learning experience. The real-time networked system implement machine-to-machine communicational platform.
Organizations involve managers and co-workers in deploying this machine monitoring system so as to encourage them to provide valuable input and also receive clear and simple directions to implement and use them on the regular basis. This would also help the rigid workers to understand that this system is too to help them and not hinder their current state of work.
This typical part also involves installing the large display screens for showing reports for machine utilization. This visualization creates a strong impact to analyze the results faster and rationally.
Once this monitoring system is installed and works as expected, the shopkeeper can further deploy additional sensors to customize the dashboard and reports to achieve additional targets.
IIoT and Cloud Computing
Cloud computing and Big Data are no more in the shell. Everyone has read about it at some or the place. These two elements or rather, technologies, are at the core level of Industrial IoT. The concept behind cloud computing is a computer processor placed at remote location runs a specific application or software rather than running it on each user’s computer. User can interact with the system via a network on the cloud. Most of the times this network is Internet.
Since the storage and processing capacity of the cloud is unlimited, it provides more economic, convenient and secure storage alternatives. The growing storage capacity can also be met as the cloud is expandable.
In connected IIoT, data is expected to flow to and from the connected devices. These streams of data usually get larger with time and that is when Big Data comes in existence. Integration of Big Data into Industrial IoT can help to generate, access and gather the huge amount of data.
For example, a specific CAM programming algorithm is more efficient at removing the most material with least amount of energy. In such cases, programmers can be notified regarding this option when cloud-based programming resources are enabled.
Condition Monitoring & IIoT
Industrial Internet of Things (IIoT) has a dramatic impact on the industries just as social media has on any teenager of today, probably, even more. Teenagers do get tired and need some rest. But machines are expected to run continuously and perform optimally as long as we maintain them.
Over the years, maintenance has been reinvented. Whether it was reactive, predictive or time-based, every maintenance policy that you use conceives the mindset of your working managers. They sure are loyal to their companies and proud of the methods they use but are largely reluctant to change the same.
Imagine possessing a monitoring system that’s always on, generating automatic repair recommendations and is smart enough to auto-populate work order system. Such systems may also reduce unplanned maintenance and spending on capital equipment by 90%. All these is possible in today’s age by the means of sharing machine data and following the initial repair alerts that such gateways detect.
The idea of replacing process with automation, and experience with smart system may seem impractical to novice entrepreneurs but implementation and applications of IIoT are proving them all wrong. Information is extracted and consumed by every little thing around you.
You may not implement such systems now, but someone else is already using it or will be using soon. They are looking for ways to improve machine efficiency, exploit vulnerabilities and receive what they expect from the machines. Efficiency application of technology and Internet plays a very vital role in such strategies. And the first ones to implement these, wins by huge margin as there are no second chances in the industry. The second prize winners are kind of fishermen who drive where the fish were day before yesterday.
With Internet available everywhere and data moving to and forth every second, how can you afford to not use such amazing condition monitoring systems that provides valuable insights, at by itself!