UEM SUSTAINABILITY CIRCLE 2024 – Proud to participate in the Sustainability Circle hosted by UEM Edgenta! It was an honor to connect with industry leaders to discuss ESG sustainability reporting and materiality assessment.
We showcased our Easi solutions, designed to tackle manufacturing and building challenges while promoting sustainable energy savings through demand-based HVAC optimization and reducing carbon footprints.
FEBRUARY 28, 2024 | MAINTENANCE EFFICIENCY, EARLY FAULT DETECTION, DATA ANALYTICS, MACHINE LEARNING, MEAN TIME TO REPAIR
Introduction
In the fast-paced world of industrial maintenance, staying ahead of equipment failures is crucial for minimizing downtime and maintaining efficiency. EasiPCM, a cutting-edge system powered by IIoT (Industrial Internet of Things) data analytics and machine learning, is transforming how businesses approach equipment maintenance. This innovative system not only simplifies the maintenance lifecycle but also significantly reduces Mean Time to Repair (MTTR) and overall downtime.
The Challenge of Unexpected Downtime
The cost of unplanned downtime in critical machinery can be significant. Traditional maintenance strategies often fall short, leading to costly, inefficient reactive maintenance.
Tanand EasiPCM AIoT offers a comprehensive solution that goes beyond mere fault detection. It integrates a lightweight CMMS, leveraging real-time data for effective maintenance management, thus minimizing downtime and extending machine lifespan.
EasiPCM also employs automated reminder alerts. These alerts are conveniently delivered via Email or EasiBot, an Assistant ChatBot designed for seamless communication. Additionally, the system is capable of automating Work Order Creation through API integration with your existing Computerized Maintenance Management System (CMMS). This feature streamlines the maintenance process, reducing manual workload and enhancing efficiency.
Advanced Early Fault Detection with IIoT and Machine Learning
The optional integration of IIoT sensors with machine learning-based data analytics elevates EasiPCM’s capabilities. This combination allows for multi-dimensional comparisons between historical trends and live data streams. The result is an advanced Early Fault Detection (EFD) system that alerts users to potential issues before they escalate. By accurately predicting equipment failures, EasiPCM drastically reduces the time spent on downtime management.
Data-Driven Maintenance Decisions: Utilizing actual machine runtime data, service intervals, and predictive health scores, Tanand EasiPCM AIoT facilitates timely and necessary maintenance activities.
Comprehensive Monitoring: The system integrates various data sources, including alarm and event logs, and inputs from AIoT sensors like vibration, temperature, noise, and spikes, for a complete understanding of machine health.
Efficient Predictive Maintenance Scheduling: Its automated, data-driven approach refines preventive maintenance into predictive maintenance schedules, ensuring maintenance activities are neither excessive nor inadequate.
Just-In-Time Maintenance Approach: This approach minimizes unnecessary interventions, reducing downtime and maintenance costs.
Spare Parts and Supplier Analytics: Deep insights into spare parts lifespan and supplier performance enable informed decisions, enhancing reliability and reducing costs.
Optimized Operations and Maintenance
EasiPCM is not just about early fault detection; it’s about optimizing your entire maintenance strategy. The system addresses the common challenges of over-maintenance and under-maintenance faced by facility maintenance teams. Whether running a building or a production manufacturing plant, EasiPCM enables teams to operate more efficiently. By minimizing unnecessary maintenance while ensuring critical issues are addressed promptly, EasiPCM ensures that your operations run smoothly and without interruption.
Conclusion
Tanand EasiPCM AIoT represents the future of industrial maintenance. By combining AIoT with advanced data analytics and seamless integration capabilities, it offers a powerful solution for predictive maintenance. Adopting this technology means embracing a more reliable, efficient, and cost-effective approach to machine maintenance.
SEPTEMBER 15, 2021 | REAL-TIME LOCATION SYSTEM, LOCATION SYSTEM INSIGHTS, AUTOMATION INSIGHTS
As digitalization and automation are the trend-setting developments surrounding industry 4.0, it is essential to adopt a centralized intelligent system to help improve and sustain the work of humans and machines.
A real-time location system (RTLS) is one solution that has received much attention to be a cost-efficiency solution. It has made a significant contribution to the overall industrial environment, but how does the implementation of RTLS significantly contribute to your industrial environment?
There is a critical ingredient to success when it comes to efficiency improvements: data.
An effective industrial environment is more of a guessing game than an intelligent and efficient operation without real-time data. The decisions you make would not be known if they had a good impact until weeks or months after the changes were implemented. This is where RTLS eliminates the assumed factors of your operation by delivering quick real-time data of your industrial environment.
Inventory/ Asset Tracking
Keeping track of critical assets/inventory is crucial for your manufacturing factory. Manufacturing pieces of equipment is essential for the company, and they are considered an expensive asset that needs to be maintained and located at all times. Inability to track your assets/inventory can disrupt the company production efficiency and production line.
Production Lead Time
In a conventional factory, workers must pick and pack assets by searching through racks and shelves, sometimes spending a longer time when certain assets are misplaced. When manual asset recording processes are used, it is more prone to errors with time delay because assets are usually not recorded immediately when it reaches the warehouse.
Material Shortage and Downtime
When a material run-outs at any production station, it causes a line stop and loss of productivity. It takes time for workers to respond to them and this also results in coordination breakdown.
Industrial Safety
Globally, industrial safety is becoming more critical, with government and regulatory bodies enacting higher safety standards that businesses must comply with. At times, manual staff tracking and accountability are highly inaccurate during emergencies. Moreover, the process is also time-consuming, and due to industrial sites typically in a large area and workforce, it is impossible to act urgently.
The benefit of RTLS:
Protecting assets and equipment with real-time information
Increasing production lead time by accurately locating assets and recording necessary asset data quickly
Improving efficiency between production workstations and monitoring work in progress
Monitoring a large area of industrial environment activity to monitor workers’ safety and hazardous area
RTLS Technology (BLE/ Active RFID/UWB)
RTLS configuration varies widely depending on the type of facility in which the technology is employed. With various components of RTLS technology such as Bluetooth Low Energy (BLE), Active RFID, and Ultra-wideband (UWB), it sends the data signal to the server to determine the location of the devices. Each component varies in ranges, accuracy, and battery lifetime to suit the industrial environment.
The choice of the most suitable technology depends on several factors:
(Precision) requirements for the system
The conditions on site
The number of assets to be tracked
Budget
Ready to implement an RTLS solution in your industrial environment? Kindly refer to the video below for more information, and contact us for a private e-meeting to start your RTLS journey, we are happy to help you to choose the right technology for your project.
AUGUST 10, 2021 | INFORMATION TECHNOLOGY, OPERATIONAL TECHNOLOGY, EDGE COMPUTING, IOT, MANUFACTURING, ENTERPRISE SOFTWARE, MACHINE LEARNING
As new technology brings operational hardware online, the border between Information Technology (IT) and Operational Technology (OT) is blurring – but what is the difference between IT and OT in the first place?
In summary:
– IT is concerned with data, in other words, IT is in charge of digital data flow.
– OT, on the other hand, is concerned with machinery, which means OT is in charge of the operation of machinery and the physical processes that carries them out.
– A useful comparison to describe their difference is: while IT happens in the office and is more often associated with software, OT happens on the production floor and is more often associated with hardware.
It’s important for key decision-makers in the manufacturing industries to comprehend the differences between IT and OT and how each domain can interrelate. Given the rapid development of Internet of Things (IoT) and its broad acceptance across the industry, manufacturers ought to spend on next-generation solutions that can bring IT and OT together to better analyze and control critical production asset and processes.
Information Technology (IT)
Simply stated, information technology (IT) is the use of the network, storage, and computing resources to generate, manage, store, and transport data within and between companies.
Some prominent features of IT includes:
1. IT has the ability to be reprogrammed.
While some technologies are built to execute a specific set of tasks (e.g. a piston), IT can be changed, enhanced, and reprogrammed in a variety of ways to suit changing networks, applications, and user requirements.
2. Other than software, IT also associates with hardware that relates to connectivity.
IT not only includes software, such as applications, operating systems, and virtualization capabilities, but also hardware, such as computers, physical servers, network equipment and so on.
Operational Technology (OT)
Operational technology (OT) can be defined as the technology that analyzes particular systems and technologies inside business operations at the most fundamental level.
Unlike IT, the hardware and software associated with OT are typically:
– intended to accomplish very particular tasks, such as regulating temperature, evaluating mechanical performance, activating emergency shutoffs, and so on;
– accomplished using industrial control system (ICS) and supervisory control and data acquisition (SCADA).
A prominent feature of OT is that OT requires human intervention at certain critical points.
OT offers a fast and direct, yet physical method, such as a switch, a steer level, or a big red button, for workers on the manufacturing floor to carry out specific operation of machineries, such as adjusting temperature or humidity level, turning off equipments etc.
On the other hand, IT is able to execute essential activities without the need for continuous human involvement – as long as the processes remain within pre-programmed parameters.
The Convergence of IT & OT – Internet of Things (IoT) Technology
Although IT and OT have traditionally been separate aspects of contemporary companies, the boundaries between the two are melting and changing due to a process known as IT-OT convergence. Since IoT technology connects assets that aren’t usually linked to the internet — manufacturers looking to transition into a smart business may now generate new efficiencies by using the flexibility and connectivity expertise of IT to the physical assets of OT systems.
IoT can convenient production floor operators by maximizing visibility of machine performance and control of machine utilization.
Using IoT to Achieve Energy & Process Optimization in Tanand
A plug-and play solution enabled by IoT and deeper analytics tailored for energy and production monitoring to improve downtime management, manpower, quality of service and reduce costs of operation.
RTMA provides accurate insights for faster decision making, empowering your production team to:
– Remotely monitor & centralize all your data in real-time to maximize facilities and resources
– Stay informedwith instant notifications by tracking server / router / application / machine downtime to know when certain thresholds or parameters are breached
– Get visual feedback into energy consumption andproduction performance by combining and analyzing machine, energy, process data, PLC, SCADA, and IoT sensor data
– Achieve predictive condition monitoring by implementing a demand-based maintenance scheduler tool that automatically prioritizes maintenance, as well as serves as a KPI measuring tool to evaluate maintenance
JULY 28, 2021 | LEAN MANUFACTURING, PRODUCTION LINE MONITORING, MANUFACTURING INSIGHTS
Manufacturers are attempting to accomplish more with less, run more efficiently, and make informed purchasing and management decisions these days. But, in order to do so, the management team must always be aware of what is going on in the production and why it is happening.
While some plant activities can be tracked manually, a machine monitoring system is the most efficient and thorough way to do so. Even so, not all data is created equal—and, let’s face it, plant managers have a lot on their plates. As a result, we’ve put up a list of the top six KPI dashboards that every manufacturer should keep an eye on in order to plan and manage effectively.
If you currently have a production monitoring system, concentrating on these dashboards and KPIs will help you get most out of it. If you haven’t yet purchased one, this is a short way to discover what Tanand can do—and why now could be the best moment to do so.
Overall Equipment Effectiveness (OEE) is crucial in identifying the percentage of planned production time that is truly productive. An OEE score of 100% represents perfect production: manufacturing only good parts, as fast as possible, with no down time. OEE score answers questions such as: At any given time, do you know which machines are operating and which are idle? How long does it take to set up a certain job? Is the target achieved for today?
You should keep an eye on the following things in particular:
Production state (Idling, downtime, producing)
Line status (e.g. running, stopped, changeover)
Parts produced (In count: good counts vs. rejects)
Availability, Performance, and Quality Loss (usually lost time within the shift, job, or part run)
OEE reports are records of what happened in the past. OEE displays are records of what is happening right now – an opportunity to change history before it happens. With plant floor electronic displays that convey OEE and other KPIs performance data in real-time, your team can address issues and solve challenges as they occur with:
Visual cues to alert when special attention is needed
Contextual information such as down time during breakdowns, target time for changeovers, and remaining time for breaks
Automated data capture for high resolution and accuracy
Supervisors making endless rounds on the shop floor will not be able to tell you this as effectively as a solid OEE system will. An effective production monitoring dashboard encourages manufacturing plants to better define the role of plant floor employees to address questions such as:
What does “green condition” mean?
When should an operator call for maintenance?
When should an operator schedule production downtime?
You can use this intelligence to take preventative measures like:
Enable operators to call for help as needed (e.g. from maintenance or supervisors)
Setting realistic delivery expectations
Planning ahead when overtime is needed
Deploying supervisors only where they’re needed
KPI Dashboard #2: Machine Downtime
You can’t increase output unless you figure out what’s slowing you down. Monitoring downtime identifies bottlenecks and provides a roadmap for improving performance, hence production monitoring system should be able to pinpoint the sources of downtime by replacing manual tracking of down time with automated tracking (track down time based on equipment inputs rather than operator tick sheets).
Automatically detect your down time using a single input from your equipment (usually an existing sensor that counts parts or equipment cycles)with sub-second accuracy using Vorne. Xl. The XL scoreboard shows down time in real-time on the plant floor and XL provides down time information to employees everywhere using patented technology and its integrated web server.
The dashboard will be able to address questions such as:
What are the causes of the downtime?
Which parts have the biggest downtime impact?
What are the down time trends, top and most most frequent down losses?
How does the down time vary by shift and part?
KPI Dashboard #3: Workforce Performance
When it comes to enhancing performance—creating accountability and providing targeted incentives—having access to data and facts is the first step.
Your best performers will be identified through a good KPI system, and you will be able to reward and recognise them. Simultaneously, it determines whether operators are efficient in completing their job by providing a historical trail of when events had happened and the details of the follow-up performed.
It is applicable to suituations where:
to ensure dynamic roster / scheduling and reduce idling when it is challenging to supervise all the operators working in a large area, e.g. cleaners or trolley operators in an airport
to provide real-time tracking for manpower efficiency when you want to ensure timely completion of tasks, e.g. when maintenance operators go into their designated zone for machine check-ups
KPI Dashboard #4: Your Plant’s OEE
OEE is most valuable when it
(a) categorizes causes of lost production time,
(b) as accurately or brutally as possible,
(c) as a basis for improvement activity.
It’s representative for how your equipment is running, and that the score is improving over time.
You receive a complete picture of your production OEE when you track your plant’s availability, quality, and performance at the highest levels. You can now spot and correct problems as they arise, ensuring that your operational goals are met and exceeded.
Production Monitoring & OEE
RTMA-OEE is embedded with standard dashboards showing availability, performance, and quality management, which allows detailed monitoring at-a-glance to empower operators to meet production goals by identifying bottlenecks in real-time for continuous production improvements.
Historical Analytics Comparison Across Lines
Historical performance and production analytics help determine if jobs will be delivered on-time. Visualize, analyze and optimize actual cycle times (hourly, daily, weekly & monthly; minimum, maximum & average) of multiple machines and lines across production floors for real-time OEE dashboards and historical reporting.
We are passionate to be the technology enabler to realize world’s smartest, most optimized & adaptive buildings & manufacturing processes that save money & improve productivity through the convergence of accelerated technologies & real-time data driven analytics.