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.

Flexibility

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.

Manufacturing Reports : Why are interactive visuals important?

Manufacturing Reports : Why are interactive visuals important?

Data is everywhere in the modern-day world. Collection of data has become easier because of the increasing number of platforms to record it. However, gaining necessary insights and creating business decisions off of data which are exhibited in tables/spreadsheets is obsolete, out of date and inexpedient. Ergo, countless businesses use graphs & charts in reporting to visualize their data in distinct ways, which allow decision-makers to discern trends and patterns more rapidly and intelligibly than through simple spreadsheets. Visualizing data can benefit wide areas of business/industry, and also, the manufacturing industry is a one such essential area which can’t function effectively excluding data visualization implemented manufacturing reports. Well!! Last week, in our blog post, we have explained how to transform boring reports? & how to choose the right report? Just in case you overlooked, you should obviously take a look. Now as a series of previous blogs, this one will provide a detailed explanation on which type of data visualization, manufacturers need, to get their reporting right.

Why production reporting needs visualization?

Production managers need to answer many questions. Some of them include,

  • What is the efficiency of your production?
  • What was the reason behind the production capacity lagging?
  • How efficient is your machinery?

Answering these questions will not be easy unless production managers earn a actionable insights from the production data. But the series of numbers in rows & column will not provide a proper answers. Of course the numbers are important. But gaining important attributes from the data is much important which we cannot expect from the boring & dry manufacturing reports in the form of tables & spreadsheets. This is because industries are generating millions of data per day and they will log these data either in notepad or in log sheets. At the end of the day the data collected will simply remain as numbers & no insights can be gained from it. This is where every manufacturing industry needs data visualization in their reporting.

Manufacturing reports with data visualization implemented, allow managers to track important metrics and KPIs that align with business objectives and help them assess how far or close they are to their target. This will help them uncover actionable insights that help the business grow and actually stay in business.

Choosing the right form for reporting

Manufacturing depends on an increasing number of factors such as manufacturing efficiency, machine effectiveness, capacity, production planning, availability, and quality etc. The above mentioned factors should function as a whole for a better running of manufacturing industry. Fortunately, visual manufacturing reports furnish a feasible solution to keep an eye on not only each of these factors but also how their tie-up influences others.

But, the thing is, not all areas can be created equal in manufacturing. There are many different types, and they all have different processes & KPIs. Hence each process demands a different type of manufacturing reports. Here are the few areas & KPIs where different types of graphs / charts are used are explained.

Production Downtime Reporting

Downtime is most often associated with equipment failures or breakdown. It probably comprise of any unplanned event that causes manufacturing process to stop. Tracking downtime is important for manufacturing industry and the overall productivity depends on equipment performance. Hence it is necessary to understand the causes & impact of downtime.

Coming back to the use of charts, let us see, which types of charts much suits to visualize downtime report.

Downtime per shift

Identifying & tracking downtime in each shift is necessary to solve the defects & attain efficiency. Use of Bar chart much suits this as bar charts can display changes over time helping people to visualize trends. In terms of downtime reporting, bar charts can display occurrence of downtime for each shift.

Downtime per shift

And also, to compare downtime for each shift for each month in a single graph, Grouped or Clustered Bar chart can be used.

Downtime shift report

By the way, these charts can also be used to view downtime per machine/equipment.

Runtime vs Downtime

Runtime refers to the time in which the machine keeps running for without any repair or shutdown.

The comparison of overall runtime and downtime can be done using PIE Chart. This is all about showing a part-to-whole relationship.

Runtime vs Downtime

Downtime by reason

All Downtime will not come under unplanned event. Downtime can also be planned. So identifying & comparing the reason for downtime is as important as understanding the cost of downtime. This provides an actionable insight not only to optimize the downtime but also keeping it under control by maintaining machinery.

As mentioned earlier, the reasons for downtime should be compared to optimize it, and this can be done using PIE Chart. No other charts can perfectly visualize the comparison of data unless it is PIE chart.

Quality reporting

In order to maintain low production costs and high profitability, it is vital to oversee & handle the scrap rate. Scrap rates compute the ineffective/malfunctioned assemblies or production of an output product which cannot be restored/repaired and as a consequence, it is thrown away or abandoned. Below standard raw materials which is serving as a deterrent, incautious framework strategy, out of order machines or ineffective production operators are the main reasons for scrapping.

Keeping an eye on excessive scrap rates of specific machinery or production group, production managers can do their best to detect the root causes for it and catch the necessary measures to avoid or prevent scrapping.

In terms of reporting quality, Stacked Area chart & stacked bar chart are suitable.

Stacked Area chart can be plotted for scrap rate by each product category/equipment. The same can be done using Stacked bar chart that is each stack in a bar represents each product and bar can be plotted against time.

Scrap rate by product category

This helps in identifying the equipment / product which produces high amount of scrap rate. So that, quality manager can take necessary action to avoid the defects.

A production manager can identify the product category with the highest scrap rate and start analysing further from here.

Good Parts Yield

If production managers are intended to compare the good parts & defective parts produced, it is better to use Pie chart which will clearly picturize the part-to-whole relationship between both.

And also, to compare the good parts yield in shift wise, they can choose stacked bar chart.

Good parts vs Defective Parts

Performance Reporting

Assessing the factors which cause production to run below the optimal speed is much important that is understanding the performance of industry or production line. Performance KPI takes into account of issues such as machinery malfunctions and unplanned shutdown which causes huge impact on industry’s production line.

To map & visualize performance, Clustered Bar chart & gauge chart will be the suitable one. While clustered chart compares planned quantity & actual quantity produced in each shift / produced by each machines gauge chart displays overall performance as percentage. This helps manufacturers understand, track & analyse the overall performance of machinery in each shift & performance loss.

Performance

Productivity Reporting

OEE is a global metric in terms of measuring efficiency & overall productivity. Enterprises should use modern visualizations to present OEE data in a way to assist the executives to come up with actionable insights. This highlights the Overall Equipment Effectiveness (OEE) and its associated KPIs that identifies the percentage of productive manufacturing time for an organization operating in multiple shifts.

OEE by Machine

Bar Graph can be used to display the Overall Equipment Effectiveness (OEE) for the selected machines over longer time periods.

And also, Bar chart can be used to track Availability, Performance & Quality.

Production by Shift

Stacked bar chart can be used to map & compare production by each shift over time.

Production Volume Reporting

A good production volume is one that satisfies demand but does not leave too much inventory in stocks. It is an overview of what Industries are able to produce in a month, a year or a specific time period. By comparing production volume data with the previous time period, it will be easy for production managers to track & stop anomalies & progress.

To visualize which machine makes up for which percentage of production, Line chart will be the suitable one. This is because, it can perfectly picturize the performance & importance of each machine by spotting the trend.

Production Volume

Capacity Utilization Reporting

Capacity utilization measures how much of the industry’s available capacity they are actually using on production line. The thing is, they should boost the capacity utilization with an intent to make machines work at an ideal cycle time. So that, they can decide whether to scale production or identify any defects in the process.
Capacity utilization can be perfectly plotted using Line chart. This helps them know, the capacity utilized by each machinery over time.

Hope this article provides you a idea on perfect implementation of data visualization manufacturing reports in Industry.

Hence, each type of visualization carries a specific role in Business / Industrial reporting and analysis. To make the reporting more simple we have added a support of incorporating data visualization types into reports in Bevywise IoT Platform.

Try to sign up with our IoT Platform at our free trial set up & get utilized with the new form of reporting.

To know the complete functionality of the IoT Platform, request a complete demo now.

Unlock the True Potential of Predictive Maintenance in Manufacturing

Unlock the True Potential of Predictive Maintenance in Manufacturing

Manufacturing Industry is the fast growing industry which is expected to continue to grow in the next few years. However, there are some complex internal challenges every manufacturing is facing today. One such challenge which has a great impact in the Industry’s production line is Downtime. Each & every production & manufacturing sector faces machine failure & downtime practically every day. People may think that the machine repair / failure / breakdown is a normal occurrence in manufacturing industry. It’s just a bitter truth when people are handling with machinery that perform a repetitive task. However, it is essential to remember / note that every second of machine running earns money. Just think a while, if machine sits idle for a prolonged time. You can’t complete your order on time, lose your reputation & finally, there will be a drawback in ROI. No matter what the failure is, it can bring about delay in overhaul, dissatisfied customers, and potential losses with respect to productivity and income. Then what is the solution for this problem?? The answer is Predictive Maintenance. In this article, let us see how predictive maintenance in manufacturing industry allows manufacturers to lower maintenance costs, extend equipment life, reduce downtime.

What’s wrong in reactive maintenance?

Industries of today most probably work on a maintenance schedule. Alternatively stated that / that is to say, they hear suggestions from the equipment manufacturers with whom they schedule maintenance. However, the previously mentioned viewpoints are not up to the level as failures and breakdowns still do occur. Ultimately, this is unimaginable & no possible way that a manufacturer can foretell every circumstances, conditions, or technique of functioning.

Besides that, some industries follow reactive maintenance, this is when machines are serviced or repaired only when they actually fail or break down. This is even worse, which is more or like waiting for a failure to happen. There is a say that, While reactive maintenance can have a place in a well-rounded maintenance strategy, it shouldn’t be your go-to for all repairs. But this is not the case in this industrial competent world. That is reactive maintenance can no longer help manufacturers in any way. This is because the unpredictable nature of reactive maintenance does not keep systems running in optimal as a new condition. And also, there will be safety issues & waste of time in finding the fix & maintenance backlog.

Why Predictive maintenance is key?

The predictive maintenance is an operation wherein the maintenance demand and prerequisite of machinery in a production line / shop floor are forecasted. That is the machine failure will be predicted & fixed before it occurs. In contrast with reactive maintenance, predictive maintenance makes use of acquired data from each machine hinge on its normal pattern of operation or performance. Any tiny or precise variation or instability with the threshold data identified by sensors will fire up subsequent alerts so that production managers can reasonably anticipate the requisite for maintenance work. In such a way, any harm or issue remains isolated, so other parts remain unaffected, and total equipment failure is avoided. And also, when it comes to preserving the lifespan of machines, predictive maintenance is the clear winner.

The major advantages, the predictive maintenance can provide for manufacturing industry are

  • Limits unplanned downtime
  • Optimize planned downtime
  • Maximize equipment lifetime
  • Reduce maintenance Expenses

Let us see the above advantages in brief.

Limits unplanned downtime

Unplanned Downtime costs manufacturers an approximately $22k per minute and almost every industry loses 10 to 30% of productivity. Therefore, unforeseen failures are one of the key players in maintenance costs because of their pessimistic influence due to reactive and unplanned maintenance action. Making use of predictive maintenance to curb this cost is demanding in highly competitive manufacturing industries. And also, ability to anticipate or foresee system breakdown before failure has a strong optimistic impact on machine running which shoots up productivity and diminishes downtime, breakdown and maintenance costs. Monitoring machines digitally collect streams of data in real-time and the data is subjected to analysis to show patterns on any provided machine. Based on identifying the pattern & historical data, manufacturers can detect the machine it means probably to encounter a failure, and for which maintenance can be scheduled effectively.

Optimize Planned Downtime

Planned downtime is scheduled time when production equipment is restricted or close down to permit for planned maintenance, repairs, upgrades or testing. Planned downtime for maintenance is peculiarly necessary for retaining critical assets well & fine, but it can also be used to diminish needless maintenance on fewer vital equipment. Each part of equipment needs maintenance at a certain point, but it can be difficult to stop production assets when you have lots of allocations to meet and machines appear to be operating without a problem. The reality is, planned downtime needs to happen, even if it appears like everything is already working properly.

Preventive maintenance can regularly be scheduled using the collected data from machine functioning & also at times where there is less impact for production order. Not only that there is also an additional benefit which is an requisite maintenance of this nature will constantly lengthen the life on a machine that would be hard, and expensive, to put back. Boosting uptime and the existence of a an equipment will eventually bring in remarkable cost savings.

Maximize Equipment Life span

Do we really know the life time of our equipments?? We may have the rough estimate how long the assets and equipment will last but how confident are we in that estimate? It could be much more or much less – and we won’t know until it’s too late. However, it is crucial to determine the equipment life and improve maintenance strategy. The inspection of machines will help manufacturers identify the condition of present production equipment and identify upcoming faults. Dealing with predictive maintenance will help them boost accuracy of equipment by the data collected on the manufacturing floor.

As machines get old and based on their degree of usage, the maintenance schedule will vary, which can be overseen through predictive maintenance. Fragment of the machine will react to the manufacturing strain distinctly across time. The ultimate rise in maintenance that is anticipated by the way of data patterns will let out when a machine set foot on a turning point on cost in opposition to performance. The requirement to put back substantial pieces of a machine ultimately, or the whole department, is made to deal with, by being capable to predict that demand and plan for it, both from a money & time view point.

Reduce Maintenance expenses

Apart from other necessary expenses in production line, a huge amount of money is spent on maintenance expenses. This will be an average of 40% in the overall revenue. We can’t sit at ease without repairing the machines / equipments but we can avoid / prevent costly repairs and or replacement of parts or machines. This is because predictive maintenance allows manufacturers to detect fault, isolate & fix issues before severe damage occurs. Moreover, since preventive maintenance is intended to pre-empt significant damage to equipment, there will be no need for extensive repair work as well as emergency servicing.

Transform PDM approach with IoT

The Internet of Things has an immense effect on the manufacturing sector, which give rise to increased automation, & more efficient operations. While the application of digital technologies can bring benefits across the value-chain, it is feasible in the area of predictive maintenance that the most significant impact can be derived. The use of sensors and data analysis means companies can pinpoint patterns in equipment condition and performance, and identify exactly when an issue might occur. Such foresight eliminates unplanned downtime, delivering substantial productivity benefits.

Moreover you can’t predict what you can’t measure / analyse. Accurate data is essential. You need to evaluate your ongoing production status, or set up a threshold of data on machine performance. To perform this, OEE ( overall equipment effectiveness) , an industry standard can be used. This lends a hand in examining each machine to check the performance degree and also to know how frequent has the machine been down, which part is undergoing issues often, how the machine maintenance can be scheduled and so on.

Hope this article provides you a better understanding & importance of predictive maintenance in manufacturing. We will be happy to discuss about your requirements at your shop floor to help you achieve successful machine maintenance.