Developing Scalable IoT Application with MQTT Broker

Developing Scalable IoT Application with MQTT Broker

Do you want to quickly and easily create an IoT implementation that meets your requirements? This is the right blog for you. Let’s see what would be the best choice to develop an IoT application easily. Building an IoT application comes with several challenges that are security, connectivity, data collection & processing etc. You already know that building an IoT application from scratch is one of the most difficult tasks. Because you must develop code for each one individually. Can you believe that a single framework contains everything you need to build any IoT application? Yes, Bevywise MQTT Broker is an IoT application framework that is suitable for the implementation of any IoT application. It provides a solution to all of the challenges mentioned above. Now let’s look at how we can configure an IoT application using that framework. 

Components required

Creating an application usually necessitates the use of components. It is essential that we have to ready with the components for developing an IoT implementation. Let’s take a look at what they are. MQTT Protocol, MQTT Clients, and MQTT Broker. When it comes to developing a large-scale IoT application, the MQTT protocol is the best choice. MQTT was found to be a flexible and scalable network protocol that is well-suited for developing an IoT application for greater implementation after taking into account a variety of developing and mature IoT protocols. MQTT Clients, which are the devices used for your implementation, can be used to develop your IoT application based on your requirements. MQTT Broker is the one that act as a middle ware to connect and communicate the MQTT clients. In that case, our Bevywise MQTT Broker also comes with Python extensions, making it perfect for building a full-fledged IoT application with high-level IoT implementation. 

MQTTRoute, a Bevywise MQTT Broker offers a free trial that allows you to experiment with the features and Python extensions to create IoT applications. You can get the free trial pack link by here – 

The MQTTRoute framework comprises all of the necessary options required to develop an IoT application. You can readily construct a large-scale IoT application with this and benefit from it. If you want to get in-depth detail about the installation and basic configuration of MQTTRoute. You can get it right here –

Now, Let us move on to the example to know more about the MQTT protocol. Assume you have two devices and various weather sensors (a humidity sensor and a temperature sensor). You’d like to send data on the humidity level and the temperature level to two different devices.

This task can be simply managed with MQTT. You must first set up a MQTT broker service. Then, on the broker, you may connect two sensors as clients and configure them to deliver data on the topics “Humid” and “Temp.” 

After that, you can connect the devices to the broker and subscribe the first one to the topic “Temp” and the second to the topic “Humid.” As a result, whenever the sensors publish the appropriate information to the broker, two connected devices will receive messages regarding humidity and temperature.

In the above example, the client sends the message to the MQTT broker, because as previously states that the clients cannot communicate each other directly. The messages sent by the clients are stored to the default database in the broker then it sends the messages to the appropriate subscribed client. The MQTT broker’s interaction with the devices was indicated in this example. Depending on your needs, developing an IoT application will require a specific UI and database. They can be found in the Python Extensions of the Bevywise MQTT Broker. Let’s look at how the Python Extensions for MQTT Broker allows you to customise an IoT implementation to your specific requirements. Here’s how these extensions can be used to create an IoT application.

Custom data storage based on IoT implementation

First and foremost, it is important to store data for an application. As previously stated, data for an application will be automatically stored in the MQTT Broker’s default database. By default, the Bevywise MQTT broker has the ability to store data in the following databases. MYSQL, MSSQL, PostgreSQL, and SQLite  However, we have the custom storage extension for you if you need advanced storage for developing your IoT implementation. If your IoT application necessitates the use of other advanced databases, you can specify the name and port of the database and use it in your implementation. For my IoT implementation, I’m using an elastic database through the use of the custom storage option. Because I want to analyse large amounts of data quickly and in near real time, which the Elastic Search database allows me to do. 

Let’s see how to configure the elastic search database here:

  • Make the necessary changes in the data_store.conf folder first. Set the DATASTORE option to CUSTOM after enabling the CUSTOMSTORAGE option.

  • The database’s PORT number and the INDEX NAME, which is the name by which you want the data to be stored and is specified here based on your needs.

  • We have commited the configuration files and the python extensions file in Git. Please refer to the data_store.conf folder and perform the above procedure using the link provided here.

  • After that, set up the folder. The elastic search connector was used to set this up. Refer to the code below for a better understanding.

  • The websocket process is used to display stored data in the user interface. This will be useful when implementing a custom UI.

  • You can refer the extension files here –

Crafting your own UI

The data is usually stored in a MQTT broker before being sent to the appropriate subscriber. But how can we be certain that the data is arriving and that the process is proceeding? That’s why we have a user interface for viewing messages between clients. By default, the Bevywise MQTT broker’s UI is useful for extracting data from devices, but you can also customise your dashboard and widgets here. However, if you want a completely different UI for your IoT implementation, use our Custom UI functionality for your high-level IoT application, which is one of the python extensions.

You can refer the extension files here –

If you want to develop your own UI code based on your requirements for any IoT implementation, then insert it in a folder. The code below is an example of how to see data in a line graph format for my IoT application; kindly refer this too.

Reference code for line graph

xaxis: {
type: ‘date’,
range: [olderTime, futureTime]
Plotly.relayout (graph_id, minuteView);
Plotly.extendTraces (graph_id, update, d)



This UI reference code is for live temperature monitoring application. Plotly provided this reference code. It takes the temperature of a room and displays it in a user interface. We can view it through the line graph’s output in this case.

Configure scheduler to generate alerts

We’ve already seen how to create your own database and customise the UI to view the data the way you want it. Taken the example given below, the room temperature monitor, and we’ll look at how to create conditions, alarms, alerts, and warnings in it. To do the above, you’ll need to use a custom Scheduler. This is also one of the Python extensions in the MQTT Broker.

You can refer the extension files here –

Create your code based on your IoT implementation and insert it into the #write your code here section. A small example of the scheduler option is provided below, and you can write your own code to suit your needs.

Reference code for Alerting high temperature in room

def schedule_conf( ):





{‘OnceIn’ : 5,‘methodtocall’ : fiveminschedule },

{‘OnceIn’ : 10,‘methodtocall’ : tenminschedule } ] }

if ( p_avg < data3 [‘msg’] [‘message’] [0] ){

document.getElementById (“Alarm”).innerHTML=data3 [‘msg’] [‘message’] [0] + “ALERT!” + “Temperature High”;


return schedules

The above code represents the condition applied which aggregate the temperature between every 5 minutes and 10 minutes schedule data and also refers to the alert setting when the temperature is high in the room. The data from the scheduler is pushed into the UI by the conditions listed above. If the temperature in the room is too high, we will receive an alert message via the UI. This way, you can easily configure it based on your needs to suit your IoT implementation. 

Enabling Advanced Authentication

Let’s take a look at MQTT broker security now. The data security in MQTT Broker is excellent. It is dependent on the security of TLS / SSL. However, your data still requires security, and we offer Custom authentication if you think security is essential for your IoT application. Custom authentication functionality in Python extensions will prove to be beneficial. Because, Bevywise MQTT Broker provides custom authentication functionality, allowing users to integrate any central IAM and SSO for your big level IoT implementation & for managing lot of users in your application based on your requirements.

Let’s see how to configure authentication in broker.conf folder


You can refer the broker.conf and extension files here –

# Request Retries Count

requests.adapters.DEFAULT_RETRIES = 3

# Request URL

url = “”

# Request Timeout

request_timeout = 0.1

# Request Method

request_auth_method = “POST”


When we manage a large number of users, as previously stated, if one of them forgets or mistypes his password, you can specify how many times you can try again in the requests.adapters.DEFAULT RETRIES field. This field’s default value is 3. You can change the count based on your IoT implementation. You can enter the URL of your authentication landing page in this field, “url = “”. This validates your attempt to connect using with your login credentials.

All of the functionality described above is provided by the Python extensions in  Bevywise MQTT Broker. With these, you can easily set up a large-scale, flexible, and scalable implementation of your IoT application.

In our MQTTRoute, all python extensions were pushed to Git. Use this link to refer to all of the folders –


To develop a scalable IoT application, start by downloading the free Bevywise MQTT Broker.


For the detail information about python extensions to develop any scalable IoT implementation, refer this link provided here –


On premise vs Cloud  MQTT Broker – Which is best for your IoT implementation?

On premise vs Cloud MQTT Broker – Which is best for your IoT implementation?

Key thoughts for choosing Cloud or On-premise MQTT Broker

Choosing between cloud MQTT Broker and on-premise MQTT Broker is a major decision that should be taken carefully and deliberately. This blog is for you if you are about to make this decision but are concerned about security or privacy and want to have greater control over your data. This will help you in comprehending the distinctions so that you can make an informed decision for your business. To make the best decision for your organisation, consider the following factors: deployment, control, security, scalability, and compliance. These factors will help you in determining the best approach for your application development.

Cloud Hosted MQTT Broker Vs On-Premise MQTT Broker 

You have improved security, performance, control over how your data is utilised, and who has access with an on-premises MQTT broker. You can also make changes to security settings yourself rather than having to wait for someone else to do it.

When employing cloud services, however, scaling up and down is more easy as needed. Both approaches bring something different to the needs of the organisation, but only after deep evaluation can you determine which solution is best for your enterprise. When deciding between an on-premises and cloud solution, you need to consider the following points:

On-premise Vs Cloud accordance with the following factors 


To enable MQTT communication in Cloud Hosting, you do not need to setup anything on the server. Managed MQTT brokers allow you to concentrate only on the development of your application, freeing you from the burden of server administration. Manage and maintain everything on your server with an on-premise MQTT broker. The solution provider handles managing the solution and related processes while using on premise.


Streamline your IoT application development with cloud hosting by controlling and managing your devices via REST based APIs from the manager application. Control & integrate your IoT solution with your ERP or business management applications. In on-premise your data, security, and privacy are all in your complete control. Your enterprise is entirely responsible for maintaining uptime and troubleshooting downtime.


Secure and safe handling of your data, as well as secure connection and communication of your devices, are all provided by dedicated cloud hosting. Compliant with security standards in data management and to ensure that your hosted information is protected without compromise. When you store your data on-premises, you have complete control over the security and privacy of your information.


On-premise solutions can be accessible remotely, but they frequently require third-party assistance. If network problems occur and your Internet connection is lost, you can still access your data using on-premise solutions. In terms of cloud, when you wish to extend your business, establish a new site in any country. In minutes, you may increase the capacity of your server. It allows data to be accessed from anywhere in the world. This gives you the freedom to work from anywhere at anytime. 


A major advantage of cloud implementation is scalability. You can adjust your on-demand consumption as needed, allowing you to scale up as your business grows. Cloud solutions provide more flexibility because they may scaled up and down on demand to meet the needs of the business. Cloud MQTT Broker is always ready to serve any business-critical IoT solutions with its scalability and reliability. To keep up with usage or demand, on-premise implementation requires further hardware or software upgrades.


Enterprises that establish the broker in On-premise, they are responsible for the server hardware, power consumption, and storage costs. By choosing to use the cloud computing model, you only pay for the resources you use, with no maintenance or upkeep costs, and the price adjusts up or down depending on how much is used. You don’t have to worry about server hardware, or maintenance when you use the cloud.


After gaining clarity by reviewing the above factors to fit your needs, you can easily determine which plan you require. On-premise vs cloud plans have different benefits. Both of these can be very beneficial to your business. 

The basis of the IoT is the connectivity and the remote control.  The most feared part is the security. However, the dedicated servers provide much more secure options equivalent to something that you get on On-premise.  Unless you have limited network connectivity for your factory in your industrial area, we would recommend a cloud hosted for a hassle free operation.

To get started with your IoT deployment, Sign-Up for a free trial now.

Kindly reach support if you have any queries.

Understanding MQTT Protocol Packet Format

Understanding MQTT Protocol Packet Format

MQTT protocol communicates by exchanging a series of predefined MQTT control packets. The MQTT packets consist of up to three parts in the following order as a 2-byte fixed header that appears in all MQTT packets, Variable Headers, and Payload that appear in some MQTT packets. This document describes how to format an MQTT Message or Packet.

MQTT client to MQTT protocol

MQTT Protocol Packet Types

Types of MQTT Protocol Control Packets are:

  • CONNECT – Fixed Header / Variable Header / Payload – MQTT Client requests a connection to a Broker.
  • CONNACK – Fixed Header – Acknowledge connection request.
  • PUBLISH – Fixed Header / Variable Header – Publish message.
  • SUBACK – Fixed Header / Variable Header / Payload – Subscribe acknowledgement.
  • UNSUBSCRIBE – Fixed Header / Variable Header / Payload – Unsubscribe from a topic.
  • UNSUBACK – Fixed Header / Variable Header / Payload – Unsubscribe acknowledgement.
  • DISCONNECT – Fixed Header – Disconnect notification.
  • PUBREL – Fixed Header / Variable Header – Publish release(QoS 2 publish received).
  • PUBACK – Fixed Header / Variable Header – Publish acknowledgement.
  • PUBREC – Fixed Header / Variable Header – Publish received(QoS 2 publish received).
  • PUBCOMP – Fixed Header / Variable Header – Publish complete.
  • SUBSCRIBE – Fixed Header / Variable Header / Payload – Subscribes to a topic.
  • PINGREQ – Fixed Header – PING request.

MQTT Packet Sizes

The fixed header field consists of the control field, and the variable header contains the packet length field. The minimum size of a packet length field is 1 byte, which is for messages less than 127 bytes.

The maximum packet size is 256 MB. The minimum packet size is only 2 bytes with a single control field and a single packet length field. Smaller packets less than 127 bytes have a 1-byte packet length field. The Packets greater than 127 and less than 16383 use 2 bytes, and so on. 7-bits are used with the 8th bit is the continuation bit.

MQTT Packet size

Control Field

The 8-bit control field is the principal byte of the 2-byte fixed header. It is divided into two 4 bit fields and contains all protocol commands and responses. The first four most important bits are the command or message type field, while the remaining 4 bits are used as control flags.

control field structure

Control Flags

While there are 16 possible flags, a limited is used. The Publish message makes the most use of these flags. The duplicate flag is used when a message is republished with QoS or 1 or 2. QoS flags are used when publishing to indicate a QoS level of -0,1,2. The Retain Message flag is also used when publishing a message.

Remaining Length

The Remaining Length is the number of bytes left in the current packet, including variable header and payload data. The Remaining length does exclude the bytes used to encode the Remaining Length.

The Remaining Length is encoded using a variable-length encoding scheme that uses one byte for values up to 127. The least seven important bits of each byte encodes the data, and the most important bit is used to indicate there are following bytes in the representation. Thus, each byte encodes 128 values and one “continuation bit”. The greatest number of bytes in the remaining length field is four.

Size of the remaining length field

Variable Header

Some types of MQTT control packets have a variable header component. Variable-length header fields are not always present in MQTT messages. Some MQTT message types or commands require this field to carry additional control information. It remains between the Fixed Header and the Payload. The Variable Header will vary depending on the packet type.

Example: MQTT Connect Message Structure

As an example, let’s take a look at the details of the CONNECT message packet in the Bevywise MQTTRoute / MQTTBroker.

After establishing a connection between the MQTT client and the broker, the first packet must be a CONNECT packet. The CONNECT packet only needs to be sent once over the network connection. The second CONNECT packet sent by the MQTT client is ignored and disconnected.

Fixed Header

Fixed header

Variable Header

The variable header must have four parts. They are the protocol name bytes, protocol level, connect flags, and keepalive.

Protocol name bytes

MQTTRoute will disable false protocol name.

Protocol name bytes

Protocol level

The protocol level for MQTTRoute is 4, other values lead to disconnection.

Protocol level

Connect flags

This field indicates the presence or absence of data in the payload.

Connect flags

Keep Alive

The MQTT client should send control packets that do not exceed the value of the defined Keep Alive. The Keep Alive value depends on the duration of the control packet of one transmission by the client.

Keep alive

MQTT Protocol Payload

The payload contains the MQTT client credentials (username, password, etc.). The client ID must be unique for each client. The broker responds with a unique client ID for each client. If you send a client ID in an empty field, the client will be rejected. The following fields must be filled in the following order: Client ID, Will Topic, Will message, username, password.

The above fields must be in string format. Any packet that does not send a CONNECT packet after a reasonable amount of time will be rejected by the broker. After successful above validation, the broker will respond in 2 format

  • Check if the client already exists. If so, the broker will respond with the disconnection.
  • The MQTT Broker will send a CONNACK packet with zero value.

After successful CONNACK, the broker will do a keepalive monitoring regularly.

To know more about the MQTT messages or packets structure, do visit the MQTT Developers page.

To know about the format of the MQTT-SN packets, visit the MQTT-SN Developers page.

Download the free version of the MQTTRoute now to validate all the features.

You can upgrade to the premium version of MQTTRoute for the full-fledged functionalities after your free trial period.

7 Key Benefits behind Digital transformation

7 Key Benefits behind Digital transformation

“Produce More with Less Resources”, is the key of all the Industrial revolutions over the centuries. The current revolution is expected to provide a leap forward in terms of efficiency.  Live tracking of performance, WIP,  Production Control with the reduction of paper and removal of duplicate manual efforts are key to success in this era. Digitizing and transforming the shop floor is going to be the effort involved to achieve the above. Let us explore in detail about functional areas that will be improved on implementing the digital transformation. Here is the top seven benefits of digital transformation.

Improved Efficiency

Manufacturing companies make large investments in machinery and they need to achieve the maximum returns on their investment in a short span of time. Improved efficiency is one of the key benefits of digital transformation. So manufacturing industries can expect a high level utilization and performance with the help of digital transformation. It reduces production losses, achieves greater competitiveness and improves machine utilization.

The reliability of manually estimated overall equipment efficiency will not be fair at all time. Hence they need a production monitoring solution that estimates the essential KPIs with the real-time status. The right OEE software will provide a real-time insights into production, improving performance & operational efficiency.

Optimal Work Load

Optimal Work Load is one of the most considerable metrics. Especially resource allocation, scheduling and assigning tasks depends upon optimal work load. Consider an example, In the early period of business, filling documents manually can be quick & quite easy. However, when the business scales up, manual data collection has become very cumbersome. It is important that you need to file, find and store documents in a quick & effective way. When you decide to assign an employee, it will be very time-consuming and its access time will be too long. However, when you deploy digital transformation, all data can be effectively stored and retrieved in minutes. Even it is a smart way to display a report. Finally, Digitalization will be the best solution & right way for optimal work load.

Flawless Data Collection & Storage

Manufacturing industries need to implement several process improvements in order to guarantee high quality products and reduce costs. Industries are realizing the essentials of flawless data collection to improve operational efficiency. The process of data, in fact, provides customers with highly effective tools in evaluation options and traceability. Data Storage is useful because the past data analysis helps to make decisions in a difficult situation. In a simple term, digital transformation converts raw data into meaningful insights. It helps to make the right decisions at the right time.

Track Materials Easily

The journey of raw material to production goods is an important process in the manufacturing unit and tracking it seems to be a difficult one. This is because the end to end flow will decide the profit of the entire industry. Monitoring & measuring the raw material usage, bad quality outcomes, the progress of final products to enter the sales market are the most responsible & complex processes in the field of manufacturing as errors may rise at any phase. Tracking & measuring such process manually will not be accurate. However, Digital transformation provides a smart way tracking of end to end system without any paper work enabling easier tracking of materials.

Production Co-ordination

One of the biggest drawbacks in traditional manufacturing is the lack of proper communication medium. This reflects on the outcome of product and the quality of work. However, production coordinator needs to ensure that the production department meets its quality standards & their production target. Without proper & effective communication between departments, it is impossible for them to coordinate their team & get effective results. Hence, in recent times, the emerging technology of using mobile & software applications will simplify communication and enhance collaborative work. This will also ensure the flexibility of knowledge sharing for industrial growth.

Increased Profits

The overall global economy depends on the manufacturing industry. Moreover, the profit of manufacturing industry is a huge key in the financial market. But the overall profit will get disrupt  with some factors like low machine utilization, downtime, worst OEE, manual tracking & manual performance management.

However, the above challenges can be simply solved by digital transformation. It provides an overall picture of the company from financial to inventory. It helps to create a more stable, predictable production environment. Tracking overall equipment efficiency over time is the foundation for improving production line performance and process quality at the same time.

Resolve a hidden factory

The first step of productivity is to discover a hidden factory. The concept of the hidden factory was primarily focused on quality, especially the waste and costs caused by bad work. Some of the hidden factors are mentioned below:

  • Schedule Loss
  • Availability Loss
  • Performance Loss
  • Quality Loss

All these factors can be rectified with the help of smart OEE tools.


Digital transformation enables a remote control of an entire manufacturing processes. So many industries already started using digital transformation technologies for proper stock management, human resources management, scheduling & utilization. Still, there are so many areas that every manufacturer should concentrate on. Manufacturers should highly adopt digital transformation as it enables the use of more flexible technology to transform the entire factory.

Hope the above listed benefits of digital transformation provides you the better understanding on why to implement it.

Do you have any requirements?? We will provide you a customized solution specific to your needs.

Six ways you can Improve Productivity in Manufacturing

Six ways you can Improve Productivity in Manufacturing

Productivity is an ultimate goal of the manufacturing industry. Especially, high production on a short span of time without any bad quality is a big dream of an Industry. However, to achieve this, the manufacturing industry should think of some key factors like people, process, digital maturity, and good management. Productivity Loss is an addressable hotspot of success. The key issue which every industry faces is the productivity loss which results due to variation of estimation time to execution time, bad quality products, worst raw material, improper Visibility, no schedule, no measurement metrics, unoptimized process, & cost inefficient.

By using the 6 ways mentioned below, you can definitely improve productivity. Let us have a deeper look in it.

Analyse and Understand Availability Loss

The first & foremost is the analysing and understanding about failure which will almost help you choose the successful way. Similarly improving productivity where productivity loss actually occurs is a major point. Losses are activities that absorb resources without creating bringing any value to the organization. The difference between Planned Production Time to runtime is called availability Loss. Mostly Equipment failure & Setup Adjustments are key factors that comes under an Availability Loss. A simple solution is the measurement of OEE which helps to rectify the problem.

Isolate Slow Performing Machines

The Slow and worst performance of the machines will have a heavy impact on productivity loss. It is necessary to analyse and measure every machine in a production line with the performance metrics. Now, compare its performance with various machines & detect slow performing machines. Then isolate such slow performing machines and so it won’t affect the workflow of the production line. Finally, diagnose & find out the reason behind the slow performance of machines and rectify it.

Start Micro Planning

Pre-planning the goal of production is an important one. Micro planning determines the detailed implementation of the identified process. On the whole production process should be segmented as a small process with proper planning. This method has a high level chance of improving productivity.

Monitor WIP (Work in progress)

WIP (Work in Progress) is a concept used to describe the flow of manufacturing costs from one area of production to the next, once the raw material arrives. Monitoring of WIP will effectively improve productivity. This is because, it is easy to rectify if there is a delay in progress.

Up skill your workforce

Collecting brains makes an effective solution that every team members like production unit members, quality members, maintenance members, superior, financial team members, selective members from various shifts, technology team and management will be gathered to conduct an effective meeting about productivity loss, Market status, financial Management, Digital Transformation and futuristic Plans. The outcome of the meeting will definitely decide Industrial growth.

Optimize the Process

Once you have retrospect, workflow and output of meeting will start identifying areas where technology and process need some update or change. Now optimize the process and redefine fine-tune architecture with the latest technologies and follow the optimized process definitively to improve productivity.

To know more….Talk to our experts to discuss about your requirements at your shop floor to improve your manufacturing productivity.

Top 5 Technologies manufacturing should adopt before 2025

Top 5 Technologies manufacturing should adopt before 2025

Adopting new technology is a growing symptom of all Industry and similarly manufacturing Industry is not an exception. Industrial revolutions have made many improvements in manufacturing and service systems. Because of remarkable and rapid changes appeared in manufacturing and information technology, industries realized the importance of adapting to new technology. These advancements are conduced to increase productivity both in service systems and manufacturing environment. In recent years, manufacturing companies have faced substantial challenges due to the necessity in the coordination and connection of disruptive concepts such as communication and networking, embedded systems, adaptive robotics, cyber security, data analytics and artificial intelligence and additive manufacturing. These advancements have paved the way for the extension of the developments in manufacturing and information technology. It is a necessary one for the manufacturing industry to maintain current trends and standard for industrial growth. Let us have a look on top 5 manufacturing technologies that every manufacturing industries should adopt.

Why to implement in before 2025?

“It is not the strongest or the most intelligent who will survive but those who can best manage change  – Charles Darwin”.

For every 5 years, technology as well as dependent Industry is continuously evolving and shaping up the future strategies. Organizations continually try to adopt new technologies to overhaul their Industry infrastructures and to keep up with the pace of changing market dynamics. Industry’s futuristic vision and mission can be accomplished only by futuristic technologies. In next 5 years especially, manufacturing industry will face dramatic changes. So it is mandatory to adopt this simple formula to succeed.

The smart way to overcome all challenges & problems in the manufacturing Industry is the optimistic use of technology.

Here is a list of essential manufacturing technologies :

    • IoT (Internet of Things)

    • Automation and Robotics

    • Predictive Analysis

    • Artificial Intelligence

    • Mobile applications

IoT (Internet of Things)

The Internet of things plays a vital role in the manufacturing industry. In today’s world, there is a heavy demand for customization with the increasing customer expectations, the complexity and many other challenges which encourage manufacturers to find new more innovative ways to remain competitive. IoT is a way to digital transformation in manufacturing. Industrial IoT employs a network of sensors to collect critical production data and it uses valuable manufacturing units to maximize productivity by maintaining production up times, reducing costs and eliminating unwanted time. IoT will help manufacturing industries improve their manufacturing efficiency.

Automation and Robotics

Automation plays a major role in manufacturing field. It is simply, without human intervention but a smart human intelligence way to get the manufacturing process done. It provides world-class quality, without any delay, while reducing errors & waste and increasing productivity.

 Automation and Robotics avoid,

  • Improper data handling
  • Skilled Labour
  • Bad Quality
  • Skilled Labour Shortage
  • Unpredictable Time Estimation
  • Approximation and Inconsistency
  • Cost ineffective

Predictive Analysis

Manufacturing industry needs effective data for decision-making and a proper way to increase productivity. Predictive analysis is definitely the right way to guide the entire manufacturing industry. It is used to make predictions about unknown future events. It uses many techniques from data mining, statistics modelling to analyse current data to make predictions about the future. It combines the power of historical data with AI and Machine learning technology to understand, monitor and identify trends, predict potential problems and it provides recommendations to improve the process and maximize performance. It avoids unwanted navigation in decision-making situations.

Artificial Intelligence

Artificial intelligence has a great impact on the manufacturing industry. It ultimately empowers manufacturing Industry to continue to be the backbone of the global economy. It is the next level of success in the manufacturing industry. Experts predict that artificial intelligence will be a game changer for the growth of the manufacturing industry.

Mobile applications

Mobile applications provide more flexibility in manufacturing and help increase productivity. It eliminates the use of paper and it helps maintain the fully paper free environment with the access of storing key documents and data on cloud environment. Manufacturers can access such data at anytime and anywhere. It boosts up employee productivity and saves so many resources.

Proactive Leaders deeply think and never stop taking initiatives. It’s your chance now. Get utilized with these manufacturing technologies.

To know more….Talk to our experts to discuss about your requirements at your shop floor to improve your manufacturing productivity.