Quantifying predictive maintenance

Quantifying the Benefits of Predictive Maintenance: 8 Benefits

Predictive maintenance (PdM) is one of the core benefits of Industry 4.0, but on the shop floor, and in discussions involving management, we need to be able to quantify the impact of PdM.

Because industrial IoT technology is constantly advancing - with better, cheaper sensors, better-secured data communication, and improved analytics - there isn’t really a golden formula for calculating the return on investment (ROI) of PdM. This is also because PdM differs greatly from one manufacturing scenario to another, being affected by equipment type, product sector, and overall facility conditions.

That said, it’s important for manufacturing operations to construct ROI models for their specific predictive maintenance implementation. This will provide a backbone for business justification, analysis of actual results, and further improvement.

 

8 Key Benefits of Predictive Maintenance

To quantify the ROI of PdM for your operation, it helps to first identify the main areas where PdM cuts costs.

  1. Reduced lost production time: PdM allows for planned downtime that is typically much shorter than responsive repairs and can be scheduled for times that are convenient and less costly. Unexpected failures become less common, increasing overall equipment effectiveness and overall line efficiency.
  2. Reduced maintenance costs: Instead of routine maintenance, which in many cases is redundant, repairs are done when needed. Having a well-defined corrective action, technicians perform in a more engaged manner instead of simply going through the motions.
  3. Reduced labor costs: Since technicians are called upon for specific and focused tasks, labor costs are reduced.
  4. Reduced equipment costs: Only the problematic parts are dealt with, saving money on unnecessary replacements and wear-and-tear of adjacent components caused by repairs.
  5. Reduced secondary damage: PdM identifies problems early on before they escalate and cause more extensive damage to equipment. Quantifying savings made by reducing secondary damage is difficult, but a widely-accepted estimate is that repairs made to failed equipment cost up to 10 times more than repairs made before failure.
  6. Reduced inventory expenses: Instead of having to keep expensive parts and materials in inventory, with PdM orders can be made only for what’s needed, cutting inventory costs.
  7. Longer lasting machinery: Since disassembly is carried out less frequently, equipment lasts longer, increasing remaining useful life (RUL).
  8. Reduced risk-based costs: Fewer unplanned repairs reduce safety risks and the chance of damage being done to other parts or equipment.

 

Factors to Consider when Quantifying Predictive Maintenance Benefits

Here’s an example of how you can visualize your pre and post-PdM repair costs in a simple manner by comparing key operational parameters:

Comparison and benefits of predictive maintenance and responsive maintenance

The chart above compares repair costs for a single malfunction. Since predictive maintenance 'caught' the malfunction early on, the damage was controlled, preventing Part B and Part C from also needing to be replaced. No production time was lost since repair was scheduled during planned downtime, and although third-party assistance was required, it was cheaper than calling for a rush job.

 

Unique Predictive Maintenance Benefits for Your Operations

Each manufacturer is likely to reap unique benefits from predictive maintenance and IoT. Beyond the measurable factors such as production time and labor costs, predictive quality and maintenance can lead to more and better products, improved safety conditions, and more satisfied customers and employees.

Factors such as cuts in inventory expenses and extended equipment life are subjective to the manufacturer so it’s important to quantify predictive maintenance benefits by taking into account the specifics of your enterprise.

 

Access the Free Guide on Predictive Maintenance in Industry 4.0
Why predictive maintenance is driving industry 4.0 - iot resource

 


Manufacturers are Leveraging IoT to Dominate Their Markets

How Manufacturers are Leveraging IoT
to Dominate Their Markets

For manufacturers, adopting new digital technologies can be a real challenge - one that requires significant planning, resources and time. IoT connectivity offers such a wide range of advantages that the abundance of options can actually deter decision makers from jumping onboard with this technology.

Despite this, the implementation of Internet of Things functionality is steadily making its way to the top of more and more to-do lists within the manufacturing sector. IoT hardware, software, platforms, and services are all being improved constantly, helping manufacturers take on the task of IoT integration with more confidence than ever before.

IoT - The Gift that Keeps on Giving

Companies that have successfully introduced IoT technology into their manufacturing operations are experiencing a host of benefits from improved energy efficiency to the production of better quality products.

IoT Manufacturing BenefitsA connected packaging machine is one area in which manufacturers are taking advantage of new business opportunities with IoT. 

And the advantages don’t stop there. Because IoT offers a level of connectivity that we haven’t really experienced before, this opens up the potential for new channels of income. In fact, IoT can lead to the renewed evaluation of a company’s business plan, with the knowledge that this new connectivity, access to data, and analysis capability, can completely reinvent how a company earns revenue.

The Bottom Line

Here it is: manufacturers need to make a conscious decision to be proactive about IoT and digitization in general. These technologies have so much to offer that avoiding this opportunity, or even procrastinating for too long, could mean risking losing business to competitors, and even becoming completely irrelevant as a manufacturing entity.

In an attempt to shed some light on the specifics of what manufacturers have to gain with IoT connectivity, we’ve put together a white paper that clearly discusses the matter.

Get the free whitepaper - Leveraging IoT in Manufacturing

Leveraging IoT in Manufacturing

This whitepaper offers insight on 6 of the main reasons why your company, factory or plant should consider the move to IoT sooner rather than later.


Model-Based Systems Engineering for IoT

Is Model-Based Systems Engineering
the Guiding Light to Successful IoT Delivery?

As IoT adoption and functionality advance, systems become more feature-rich, the number of connection points increases exponentially, and managing physical devices, data, and digital networks becomes more complex. Organizations will have to meet this complexity head-on in order to be able to leverage the benefits of IoT.

The pairing of IoT development and Model-Based Systems Engineering (MBSE) is growing in popularity as a way to successfully deliver IoT projects. MBSE is proving itself as a viable approach to IoT implementation because of its “Systems of Systems” approach.

Spending Quality Time with your IoT Project

At first glance, Model-Based Systems Engineering might seem like an overly-complex methodology for product teams to deliver their IoT projects as fast as possible. And yes, initially this approach might take longer than a more informal one. The catch is that rushing a product to market quickly can often lead to its ultimate demise through unforeseen defects and customer disappointment.

Moreover, while a first project using MBSE might seem to require more time, following projects are likely to progress even faster than before. Deployment times improve due to a better understanding of how to apply the principles, and thanks to the avoidance of unnecessary iterations, wasted resources, and having to deal with surprise malfunctions.

It’s important to remember that IoT projects aren’t limited to gadgets that make our lives a little easier. Autonomous travel, smart medical devices and connected machinery could all have life-threatening consequences should errors occur in the IoT system and network. Taking the extra time to perfect and evaluate a system before launch is crucial in such cases.

What MBSE has to Offer IoT

By employing Model-Based Systems Engineering, an IoT system could be built, evaluated, maintained, and improved by addressing questions like these...

  • Has a model-based engineering approach been used to specify the IoT system's requirements?
  • Does the IoT system functionality answer the user requirements?
  • Have the requirements been tested with a user group?
  • Is the IoT system's testing automated? And, what is the best way to manage the IoT testing process?
  • Are design and functionality decisions guided by analysis and simulations?
  • Is the network architecture and overall design being verified using system-level analysis?

The above questions demonstrate the fact that MBSE points to a data-driven evaluation and decision-making process.

This approach places a lot of emphasis on verifying a project across a number of domains by utilizing software, hardware, and cyber-physical IoT simulations.

Creating a Digital Twin

An exciting outcome of using Model-Based Systems Engineering for IoT is the creation of a “Digital Twin”. A digital twin is a customized high-resolution digital model that works in parallel to an actual system.

For example, a manufacturing plant could have a digital twin that precisely reproduces the dynamics of all the systems within the plant. Every process in the plant from raw materials processing and production to quality control and delivery can be monitored and repeated in the digital twin in real time. This allows for risk-free experimentation - through simulation, processes can be modified to any extent, and the results can be measured and compared.

Model-Based Systems Engineering for IoT

As with all new technologies, there is no golden rule or single tried-and-true method for integrating IoT into a product or manufacturing process. Each use case is different, and different approaches will have to be considered along with a good amount of customization and testing.

Model-Based Systems Engineering is an established engineering discipline, which means it offers a defined pool of professionals with a specific skill set. As a framework with its own principles and solutions, and because of its data-driven approach, Model-Based Systems Engineering could be extremely useful in successfully delivering complex IoT systems.

 

 


Manufacturers are Racing Towards IoT in the Automotive Industry

Why Automotive Manufacturers Are Racing Towards
IoT Product Development

We live in an age where failing to adopt new technologies can quickly make even the biggest corporations obsolete. Nokia and Motorola are two classic examples of how giants can fall if they hesitate to leverage technology. The benefits of IoT connectivity go far beyond initial cuts in costs earned from automation and data exchange. With the emergence of IoT in the automotive industry, manufacturers that successfully integrate this technology into their products can expect to enjoy entirely new revenue channels that are just waiting to be explored.

The continuous growth of IoT in the automotive industry will revolutionize the way people interact with mobility solutions, and in turn, affect the way manufacturers generate income as a whole.

The Rise of IoT in the Automotive Industry

From Software Updates to Oil Changes

Post-purchase interaction between consumers and manufacturers has always been a central part of the automotive industry. The physical nature of transport means that vehicles undergo wear and tear that can’t be predicted...or, can it?

By implementing IoT components, a vehicle’s status can be constantly monitored, allowing for predictive maintenance that preempts breakage or malfunction. IoT use cases have shown that not only does this lead to happier and safer owners, but it also generates invaluable data for manufacturers about systems and parts.

An IoT network maintains a reliable link between manufacturers, owners and repair services. In this way, maintenance schedules can be optimized, and if the car is autonomous, repairs can be made without the involvement of the owner at all.

Avoiding the Dreaded Recall

The number and scale of car recalls in the last few years has shown an alarming increase, with a significant portion being due to software issues. The economic damage of recalling hundreds of thousands of vehicles is huge, not to mention the damage done to the brand. With IoT components in cars, software updates are implemented as soon as improvements have been made, whether that’s bug fixes or efficiency enhancements.

Going Electric

The introduction of IoT connectivity can boost an electric vehicle’s market value, and seriously cut production costs. Being a benchmark within the electric car industry, power monitoring and optimization is important to both manufacturers and users. With regular software updates, and the continuous streaming of data on usage, performance and service needs, manufacturers can constantly improve their products and stay competitive.

The Self-Driving Dream

The potential advantages of autonomous cars in safety and user experience are numerous. Above all, this is a product that people want. IoT connectivity can take into account a huge array of environmental factors, and could be used with machine learning to constantly improve the performance of an entire network of cars, not to mention individual components.

Keeping up with Compliance

Changes to regulations in the automotive industry can be a major sore point for manufacturers. With IoT connectivity, vehicles and individual parts can be modified remotely to meet regulation updates on carbon emission, user experience, and for safety features such as emergency calls.

IoT implementation in Automotive Industry

Shared Mobility

We’re witnessing a dramatic change in how we use vehicles as a community. The desire to own a car is becoming less popular, and car-sharing and on-demand ride services have emerged as real crowd pleasers. Manufacturers will need to adapt to this disruption in the market to stay relevant, and the new channel of opportunity provided by IoT product development can greatly assist in making that happen.

IoT in Smart Cities, and Beyond

The benefits mentioned above are really only the tip of the iceberg as the introduction of IoT into the automotive industry will affect sectors from insurance to urban infrastructure.

This complete paradigm shift will transform cities dramatically, and will set the foundation for how we use and develop IoT technology moving forward.

 


Demystifying IoT Connectivity Protocols for Industry 4.0

Demystifying IoT Communication Protocols for Industry 4.0

The term “Industry 4.0” is all the rage right now, but how viable is it to transform existing machines and industrial equipment into a connected Industrial Internet of Things (IIoT) system? The advantages of connecting a device to the IoT are many, but like with any step that involves adopting a new technology, it’s important to be aware of those make-or-break factors that will lead to a product’s success, or failure.  Since IoT connectivity represents the backbone of the IIoT system as a whole, a lot of care should be taken when choosing the type of IoT communication protocols it will be using. 

Deciding on the right data integration protocol early on is critical for building a successful IoT system.

When implementing IoT, decisions regarding how the data is transferred will often seem overwhelmingly complex. Fortunately, standardization in data connectivity for the Industrial Internet of Things, along with advances in simulation tools, has made it much easier to make better and more informed decisions about data connectivity and integration.

IoT Data Integration Checklist

This checklist includes the 6 most important factors to keep in mind when considering which protocol to use for your industry 4.0 data integration.

1. Range

What is it?

Range describes the distances over which data is transferred between devices in an IoT system.

Why it Matters

If your desired IoT network requires transmitting data over large distances, using a protocol designed for short-range communication won’t work. Range can also be used to restrict the movement of data as a security measure by using protocols with especially short ranges.

 

2. Bandwidth

What is it?

The volume of data that can be transferred in a defined time period.

Why it Matters

Every protocol delivers data according to a defined packet size. The volume of data within a typical transmission should match the packet size that the chosen protocol can accommodate. Using packet sizes that are much larger than the data that needs to be sent is inefficient. On the other hand, dividing up large blocks of data so that it can be transmitted by lots of smaller packets can lead to unnecessary processing.

  

3. Power Consumption

What is it?

The power needed by a device to transmit data.

Why it Matters

This is a particularly important factor to take into account when designing products that rely on battery power. The power efficiency of the data transmission process will affect the battery life of the device, and in turn, operation costs.

 

4. Security

What is it?

Measures taken to protect data across the various stages of transmission, and during storage.

Why it Matters

When data moves from device to device it becomes vulnerable. Security is one of the main concerns of companies looking to introduce data connectivity to their products. Fortunately, there are many technologies in place to allow for secure IoT connectivity, including port protection, authentication, and encryption.

 

5. Connectivity Control

What is it?

The behavior of a device with regards to when, and for how long, it’s in a connected state in a typical use case.

Why it Matters

When a device is connected, it consumes power and uses up bandwidth. For this reason, some devices control when they’re connected and when they’re offline. This control over connectivity is also closely linked to how robust an IoT system is i.e. devices staying connected when they’re supposed to, without dropping off the network unexpectedly.

 

6. Interoperability

What is it?

The ability of one connected device, sensor or app to communicate with another, usually from a different manufacturer, host or vendor.

Why it Matters

In some cases, setting up an optimal and flexible IoT network will require the integration of a number of elements that aren’t always from the same vendor. Or, advances in technology may lead to the creation of improved devices that a user would like to switch in to replace older elements in an existing IoT setup. Capability with regards to interoperability is central to the value of an IoT product.  

 

IIoT Protocols at a Glance

Currently, the three most common IoT communication protocols are MQTT, AMQP, and CoAP.

MQTT - Message Queuing Telemetry Transport

Previously called the “SCADA protocol”, MQTT is a simple-to-implement, lightweight, ISO-approved messaging protocol especially useful for remote communication, and in cases of restrictive bandwidth. MQTT’s publish-subscribe, low power consumption, small size and efficient data distribution via minimized packets make it an excellent choice for IIoT implementations and mobile applications.

AMQP - Advanced Message Queuing Protocol

AMQP is an open-standard, feature-rich message queuing protocol that offers reliable and secure queuing, routing and orientation of messages. AMQP provides a high level of interoperability, allowing for a wide variety of communication patterns and messaging applications.

CoAP - Constrained Application Protocol

CoAP was designed specifically for connecting devices with constrained resources such as a limited power supply or small memory. New extensions to CoAP allow for defining and addressing several CoAP resources as a group, and reduced transfer times.

 

Step up your IIoT Game Today

So, where should you start? Well, based on the 6-point checklist above, you can begin by breaking down the data connectivity requirements of your product, as per each of the six factors. Then, select the iot data connection protocol that best suits those requirements.

For a more in-depth look at designing and delivering industry 4.0 systems integration, make sure to check out our library of free IoT resources.

Also, feel free to contact us to find out how the Seebo platform can assist you in advancing to Industry 4.0 without the risk, and without the headache.