Reduce downtime with AIoT predictive analytic

reduce downtime with predictive analytics

The manufacturer’s potential losses due to unplanned downtime and possible solutions to mitigate them were the central topics discussed during the live sharing session on April 12, 2024, in the “Sembang AIoT” live talk hosted by AIoTmission and Axiomtek Malaysia.

Below are some of the potential losses:

Production Losses: The most immediate impact is the loss of production output during the downtime period. This directly affects the ability to fulfill orders and meet customer demand, potentially leading to missed sales opportunities and dissatisfied customers.

Revenue Losses: With decreased production comes reduced revenue. The longer the downtime persists, the greater the financial impact on the manufacturer’s bottom line.

Wasted Materials: During downtime, raw materials may sit unused or partially processed, leading to wasted resources and increased material costs.

Labor Costs: Even though production may halt during downtime, labor costs often continue as employees may still need to be paid despite not actively working on production tasks.

Overtime and Recovery Costs: Once production resumes, manufacturers may need to implement overtime hours or expedited processes to catch up on missed production targets, resulting in additional labor costs.

Equipment Repair or Replacement: Depending on the cause of the downtime, there may be repair or replacement costs for damaged machinery or equipment, further adding to the financial burden.

Reputation Damage: Extended or frequent downtime can damage the manufacturer’s reputation among customers and suppliers, leading to potential long-term impacts on relationships and future business opportunities.

Overall, the losses incurred during unplanned downtime can be significant, not only in terms of immediate financial impact but also in terms of long-term consequences for the manufacturer’s competitiveness and reputation in the market.

plastic injection machine predictive analytics

Introducing the AI Data analytics to the to the Plastic injection machine as a solution to reduce or avoid unplanned downtime. 

An AI predictive analytics solution for a plastic injection machine could involve the following components:

Data Collection: Gather data from various sources within the manufacturing process, including IIoT sensor data from the injection machine itself (e.g., Vibration,temperature, pressure, cycle time), historical performance data, maintenance records, environmental conditions, and quality control data.

Data Preprocessing: Clean and preprocess the collected data to remove noise, handle missing values, and normalize the data for analysis. This step may also involve feature engineering to extract relevant features from the raw data.

Predictive Modeling: Develop machine learning models to predict potential issues or failures in the plastic injection machine. This could include regression models to predict machine performance metrics (e.g., cycle time, defect rate), classification models to detect anomalies or impending failures, and time series forecasting models to predict future machine behavior.

Feature Selection and Engineering: Identify the most relevant features that contribute to the predictive accuracy of the models. This may involve techniques such as correlation analysis, feature importance ranking, and domain expertise to select the most informative features for prediction.

Model Training and Evaluation: Train the predictive models using historical data and evaluate their performance using appropriate metrics (e.g., accuracy, precision, recall, F1-score). Iteratively refine the models to improve their accuracy and generalization to new data.

Real-time Monitoring and Alerting: Deploy the trained models to a real-time monitoring system that continuously analyzes incoming data from the plastic injection machine. The system can generate alerts or notifications when it detects abnormal patterns or potential issues that require attention from operators or maintenance personnel.

Integration with Maintenance Systems: Integrate the predictive analytics solution with the manufacturer’s existing maintenance management systems to schedule preventive maintenance activities proactively based on the predictions generated by the models. This can help minimize unplanned downtime and reduce the risk of equipment failures.

Continuous Improvement: Continuously monitor the performance of the predictive models in production and collect feedback to refine the models further. This may involve retraining the models periodically with new data to adapt to changing operating conditions and improve predictive accuracy over time. When predictive analytics is applied together with the OEE tracking system, it will ensure the process is running with full efficiency and maximum capacity.

By implementing an AI predictive analytics solution for the plastic injection machine, manufacturers can enhance operational efficiency, reduce downtime, optimize maintenance schedules, and ultimately improve the overall productivity and profitability of their manufacturing processes.

To watch the detail live detail. you may visit our youtube channel at 

AIoTmission Sdn Bhd, established in 2022 as a subsidiary of Axiomtek (M) Sdn Bhd, is a leading provider of technological training and consultancy services specializing in Artificial Intelligence (AI) and Industrial Internet of Things (IIoT) solutions. Our mission is to drive the Fourth Industrial Revolution (IR4.0) and facilitate digital transformation across Southeast Asia, including Malaysia, Singapore, Indonesia, the Philippines, Thailand, Vietnam, and Myanmar.
At AIoTmission, we are dedicated to advancing research and development in AI and IIoT technologies, with a focus on industrial applications such as sensors, gateways, wireless communications, machine learning, AI deep learning, and Big Data cloud solutions. Through collaboration with our valued clients and partners, we deliver innovative solutions tailored to industry needs, enhancing technological capabilities and operational efficiency.

Jom! lets Sembang AIoT!

We are delighted to announce the commencement of our live sharing session, titled “Jom! Let’s Sembang AIoT,” which began on May 24th, 2023. The primary objective of this initiative is to provide a comprehensive overview of our collective experiences and activities in the fields of IoT and AI. Given the rapid pace of technological advancements, we have taken this opportunity to engage the audience and solicit public comments to better understand the current trends and requirements in the realm of AI and IoT.

Today, on July 2nd, we are pleased to share that we have successfully completed our fourth live session. These sessions occur every Thursday or Friday, depending on our scheduling constraints, as we are committed to fulfilling other responsibilities during weekdays. Nonetheless, we assure our audience that we dedicate ourselves to delivering the highest quality content. Our discussions cover a wide range of topics, including real-life experiences in working on AIoT projects and development, as well as fundamental concepts of Industrial IoT and AI. We highly recommend following our AIoTmission’s YouTube channel or Facebook page to stay updated with our latest content. The most recent live session is included at the end of this post, and we encourage you to subscribe to our channel if you find the information pertinent and valuable. Hope to see you in the upcoming live channel!



Live session ” JOM! lets Sembang AIoT”  a Malaysian’s style of openly talk about technology in AI and IoT. 

OEE Tracking for Smart manufacturing with AIoT

OEE Tracking Training with AI and IoT

Overall Equipment Effectiveness tracking is one of the most classical and proven methodologies of tracking production equipment and processes. With the help of Industrial IoT and AI technology, it can be digitally transformed to meet the requirement of Industry 4.0 where connectivity and data transparency is of main concern.

RiSE4WRD for Industry4WRD 

RiSE4WRD for Industry4WRD is HRD Corp’s initiative to support the national agenda of embracing the Fourth Industrial Revolution (IR 4.0). This programme is designed to assist SMEs in the manufacturing and related sectors that have participated in the Readiness Assessment (RA) under the Ministry of International Trade & Industry (MITI), to start or accelerate their digital transformation journeys. If you have enrolled for this program, you may look out for our training program on AIoTmission IOT OEE and AI OEE HRDF claimable training programmed.

There are 3 main source of data that dictate the OEE index, Availability, Performance and Quality. By using the Iot devices and tool, data can be tapped from the machines and processes. Those data can then be calculated based on the formula in order to produce the online data of OEE index. 

By looking at the OEE index, you will know how effective or how efficient your process is running. IoT devices and tools allowed you to make this available and connect to the wanted servers or platform. The visualization is make possible at the local site as well as Cloud.

AIoTmission AIoT OEE Training provides you a very practical training outcome where after the training, you should be able to know the overall concept of IoT and AI in the application of making up the OEE Tracking system and you should be able to put that into the implementation of the system. 

There are 4 main key skill sets in the training:-

  1. IoT connectivity from sensors to the system
  2. AI application on Quality factors
  3. Data integration to databases and related production system.
  4. Data manipulation and visualization at local SCADA and  Cloud.

Book your interactive chatting session (15 mins) with our Trainer about your needs with no obligation.

Exclusive AIoT Mission Training

Exclusive AIoT Mission Training

AI and IoT are key technologies in the Era of digitalization. In the context of AIoT, AIoTmission focus on proving innovative tools in data collection for IoT and optimized AI inferencing emphasized by Intel on PC based platform to achieve the AI inferencing result with Intel core CPU. 

In this training, practical experience in shop floor data acquisition is made into practise with Axiomtek IoT edge gateway and Stack light IO module that acted as a simulation of the production process and machine’s status.

Tesla IoT edge acted as a  tool to construct and build an intuitive data collection method at the simulated shop floor.
The industrial communication protocol was introduced and IoT protocol set was taught in the training.
Cloud computing and experience was brought in as a platform for participant to realize the how the IoT cloud connectivity and as well as the dashboard’s  presented data is realised.
On the AI portion, the concept and theory behind the AI engine was introduced and Hands on in building the AI model was put into
the training for participants to get to know how the AI model is built as that is the key about the whole AI process in machine Learning and also the AI Deep learning.
We hope that this training will spark up the idea of more applications of AI and IoT in their working environment as we know the technology will be only become powerful when it is applied.
We innovate . We Apply and we sure train !

SCADA Training OEE series

On site SCADA Training on OEE integration to our client.

It was a great 5 days of training just before the announcement of endemic. Thank you to all the team members for making this happen. As OEE still stay relevant in all the manufacturing process. Indusoft Web studio was brought to the front to gather, automate and present the shop floor data. it is a successful transfer of skill to the client and they are able to expand on their own from there on!
A quick introduction, AIoTmission is a training and consultancy arm of Axiomtek Malaysia to research, to share and transfer knowledge and skill that has been accumulated in the past 25 years in the industries. One of the key focuses will be the Digital transformation in the industries or IR4 activity that require the engagement of technology such as IoT, AI and any of technology development.

Non intrusive analogue meter reading using Axiomtek AI suite

In the Era of digitalization, almost all the old apparatus in measurement is now being relooked as data analytics has become vital in many important decision-making processes.

The smart meter enables remote and automated meter reading, however, in many industries, there are still a huge number of analog or gauges in operation. Human operators need to read the meter reading and log it down to enable the data to be used elsewhere. Someone might suggest replacing those analog meters with smart meters, but most of the time those gauges are not easily touched or tempered in some critical process as it might cause some unforeseen circumstances.

As far as digital transformation is concerned, Axiomtek Malaysia provides both Industrial AI and IoT solutions based on the Intel platform in most of the digital transformation processes specifically in the area of the manufacturing industry and industrial applications. One of the challenges is being able to tap onto some analogs meters or gauges and convert that to a digital format for data analytic purposes.

In achieving the above objective, we went into using Axiomtek AIS to make a non-intrusive analog to digital meter reading based on vision AI. A camera will be located in front of the meter/gauge to generate live video stream to Axiomtek AIS. Axiomtek AIS uses deep learning approach to locate the position of meter pointer and convert it to digital value. The digital value will then send to SCADA engine for display and logging purposes.

you may look at the short video below, it shows the successful first experiment by using the Axiomtek AIS and thanks for AIoTmission team ( One of the axiomtek AIoT traning and consultancy company) in making this happen.

We look forward to any of your feedback and if you found any needs like the above situation like what we have mentioned. do contact with us at +603-77731203 or Whatsapp us at 017-9698026.  Get to know more Axiomtek’s AioT solution. visit us at :

Courses Offered

Courses Offered

We help your Business identify suitable technologies to improve efficiency especially in the area of industry 4.0 and digital transformation.  We provides AIoT consultancy and solutions that fits to the manufacturing processes.

We work with you to exploit new ideas and new technologies, and develop system that and strategies to help you stay ahead in your business. With Team of engineers, scientists, technologies, digital experts and system integrator partners, we can offer turn key system to handle any of your needs in the process of your digital transformation.

We combine this with clear commercial insight We’ve been helping businesses find ways to implement factory automation system from technology and innovation for more than 20 years. And we apply exceptional cross-sector insight to your challenges too. We can bring you ideas from many different industries to help you discover smarter solutions faster.

Courses available:-

  • Artificial Intelligent jump starter for digital transformation in manufacturing environment.
  • Industrial Internet of things jump starter for digital transformation in manufacturing environment.
  • IoT SCADA integration and implementation
  • Secure Mobile network Integration and implementation.
  • AI facial recognition in access control and People tracking 

(Artificial Intelligent) AI and (internet of things) IoT for Smart Manufacturing & IR 4: –  

(Artificial Intelligent) AI and (internet of things) IoT for Smart Manufacturing & IR 4: –  

  • ContactVision AI suite with AIS Jump starter kit for OEE

Practical training for Technicians, Engineers, and Managers to get to learn how AI can be used in the manufacturing environment to accelerate the digital transformation and improve productivity and cost. AI vision inspection will be used as a base subject with OEE ( Overall Equipment Effectiveness) to realize the use of AI in Quality assurance and inspection.

After the training, the attendees should be able to create an AI model and training the AI system to perform the AI inferencing on any objects, parts, or conditions within the 1-2 days depending on the complexity of the model with the JumpStart kit.  Deployment of the AI process will be taught in the 3 days course as well.

  • IIoT Jump Starter kit for OEE

Practical training for Technicians, Engineers and Managers to get to learn the IoT key components and protocol in terms of data collection and connectivity that allow efficient data collection, Data automation, and also Dashboard presentation of data where OEE is the model for the customer to realize the actual implementation of IIoT in the manufacturing environment.

After the training, the attendees should be able to create the data collection system with the intended connectivity devices and publish of data to the designated host for data representation within the 1-2 days depending on the complexity of the Data collection method required. Deployment of the  OEE data will be taught by using the IoT starter kit in the 3 days course as well.