Achieve data-driven smart manufacturing with subscription-based AIoT Cloud application

Achieve data-driven smart manufacturing with subscription-based AIoT Cloud application

Do you find smart manufacturing and Industry 4.0 unreachable? Digiwin AIoT Cloud connects equipment data to the cloud. With the structure of micro-services, large-scale software can be lightweight and flexible. It is the first step for factories to move towards Industry 4.0. This article will introduce Digiwin AIoT Cloud, its differences from traditional industry-specific software, and its benefits. You can learn how this cloud application assists digital transformation in the manufacturing industry.


Smart manufacturing is easy to know but difficult to implement

Smart manufacturing is a new way of factory production in response to market changes and business model alterations, such as small-scale and diversified production. Enterprises expect these outcomes could be acquired by intelligence tools: quality improvement, cost reduction, delivery acceleration, production flexibility, etc. As we know, IoT, big data, and AI are the future trends for smart manufacturing. For many SMEs, it is easy to comprehend the ideology but hard to do so. The main obstacles are the concern of the high initial cost and slow results.


AIoT Cloud is the “new weapon”

Digiwin AIoT Cloud focuses on the mobility of IIoT with the base of IoT. Based on industrial manufacturing scenarios, the AIoT Cloud integrates knowledge and manufacturing data into the software, including R&D, process improvement, manufacturing, operation, maintenance, and more. In short, it can help with on-site visualisation, merge the collected data with algorithm models, and finally develop into big data analysis and AI.

In terms of technology, the AIoT Cloud uses the micro-service architecture to split the software functions into small units. Let’s take online banking as an example. Overview of account information, money transfer, and credit card details are different microservices. The main advantage is that each microservice is independent, which is more agile and easy to update and expand. The ripple effect of development and usage problems no longer occurs.

As a result, Digiwin AIoT Cloud can solve the pain points of SME smart manufacturing development:


  1. Lightweight: AIoT Cloud focuses on small applications in specific scenarios and can be subscribed to at any time as your demand, reducing the initial costs.
  2. Real-time: Through IoT, the AIoT Cloud can collect real-time data, solve problems under abnormal conditions, and achieve effective management through instant analysis.
  3. Scalable: Based on the micro-service design of IIoT, the application can be scaled up to meet the demands of different industries.
  4. User-friendly: Based on the concept of SaaS, it provides a simple interface for different functions and service combinations. It is easy for staff to operate without training and mishandling costs.

IoT can help you to achieve all the above. Then, you can manage the factory status in real time with an app. Many networking services and IoT boxes can help with machine transformation with plug-in techniques without purchasing a new machine.


AIoT Cloud assists smart manufacturing

Next, we will learn how to use AIoT Cloud to assist smart manufacturing through practical cases. There is a machine tool manufacturer specializing in CNC lathes, milling machines, grinders, and instrument lathes. The company faced the following pain points:

  1. There are many types of equipment, and the handling of abnormal equipment is not timely.
  2. Personnel performance standards are inconsistent.
  3. On-site production is hard to control. 

Hence, the company hopes to improve on-site visualised management, work efficiency, production progress monitoring, equipment operation, equipment inspection efficiency, and early warning of abnormal equipment through Digiwin AIoT Cloud.

Digiwin assisted this company in setting up edge servers in the IT room. It can directly connect with the NC system of the on-site CNC machine and collect process parameters such as machine tool status, output, spindle speed, and magnification in real-time. On the other hand, it can connect the edge server with the customer’s existing ERP system (Digiwin E10 ERP) to dispatch the manufacturing orders to the corresponding machine.

The machine operator can check in and check out through the AIoT Cloud on the mobile phone. The edge server calculates and stores the collected OT data and integrates it with the obtained IT data (manufacturing order). Then, it transmits the data to your application in an encrypted form. The project achieves the following benefits:

  1. Real-time monitoring of equipment capacity utilization and production progress.
  2. Real-time monitoring of abnormal equipment parameters. If the parameters are abnormal, the application will notify the person in charge immediately.
  3. Analysing equipment status and the defect causes to provide decision-making references.
  4. Check in and check out the station by phone and record the personnel performance.

In addition, the company also implemented the Digiwin device-networking box to collect the parameters of the machines in real time. Besides, they place QR codes on the machines to achieve electronic inspection to avoid making up the account afterward. At the same time, the efficiency of inspection personnel is improved. After the implementation, the comprehensive utilization rate increased by 15%, the compliance with the production schedule increased by 10%, and the delivery guarantee improved too.


AIoT Cloud realises data-driven decision-making process

The AIoT Cloud not only assists the production efficiency improvement of smart manufacturing but also realizes a data-driven decision-making process. Based on the experience, AIoT Cloud helps with decision-making on these three levels:


  1. Data + Application: transparency and visibility. Visualised data shows equipment status, production status, processing parameters, etc. It supports the supervisors and managers to review the progress and goals. Example: the real-time production monitoring application, production Kanban, and war room dashboard.


  1. Data + Algorithm: early warning and control. In the processing process, through the basic algorithm and the control of the upper and lower normal line, the equipment problems can be revealed in real-time, thus the manufacturing process becomes smoother. Example: CNC spindle speed monitoring and abnormal vibration warning.


  1. Data + Model: prediction and optimization. Using big data and AI to find the best solution, improve production and avoid possible abnormal risks, such as life prediction of key components, quality analysis, etc.


Enterprises need to consider many factors if they want to move towards intelligence. Digiwin AIoT Cloud is a lightweight, easy-to-apply solution. In addition, through the cloud subscription service, you can reduce the initial cost and avoid the problem of software obsolescence. It can be revised based on user scenarios to meet the needs of different on-site positions. From it, you can improve efficiency and realize innovation in data-driven decision-making. 

Share with your colleagues and friends