Failure Mode and Effects Analysis

 

Any business in the manufacturing industry would know that anything can happen in the development stages of the product. And while you can certainly learn from each of these failures and improve the process the next time around, doing so would entail a lot of time and money.
A widely-used procedure in operations management utilised to identify and analyse potential reliability problems while still in the early stages of production is the Failure Mode and Effects Analysis (FMEA).

FMEAs help us focus on and understand the impact of possible process or product risks.

The FMEA method for quality is based largely on the traditional practice of achieving product reliability through comprehensive testing and using techniques such as probabilistic reliability modelling. To give us a better understanding of the process, let’s break it down to its two basic components ? the failure mode and the effects analysis.

Failure mode is defined as the means by which something may fail. It essentially answers the question “What could go wrong?” Failure modes are the potential flaws in a process or product that could have an impact on the end user – the customer.

Effects analysis, on the other hand, is the process by which the consequences of these failures are studied.

With the two aspects taken together, the FMEA can help:

  • Discover the possible risks that can come with a product or process;
  • Plan out courses of action to counter these risks, particularly, those with the highest potential impact; and
  • Monitor the action plan results, with emphasis on how risk was reduced.

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Spreadsheet Risk Issues

It is interesting to note that the riskiness of operational spreadsheets are overlooked even by companies with high standards of risk management. Only when errors amount to actual losses do they realize that these risks have been staring them in the face all along.

Common spreadsheet risk issues

Susceptibility to trivial manual errors

Due to the fundamental structure of spreadsheets, a slight change in the formula or value in any of their inhabited cells may already affect their overall output. An

  • accidental copy-paste,
  • omission of a negative sign,
  • erroneous range selection,
  • incorrect data input or
  • unintentional deletion of a character,cell, range, column, or row

are just some of the simple errors spreadsheet users frequently encounter. Rarely are there any counter-checking controls in place in a spreadsheet-based activity and manual errors therefore easily go undetected.

Possibility of the user working on the wrong version

How do you store spreadsheet files?

Since the most common reports are usually generated on a monthly basis, users tend to store them using variations of these two configurations:

spreadsheet storage

If you notice, a user can accidentally work on the wrong version with any of these structures.

Prone to inconsistent company-wide reporting

This happens when a summary or ?final? spreadsheet is fed information by different departments coming from their own spreadsheets. Even if most of the data in their spreadsheets come from one source (the company-wide database), erroneous copy-pasting and linking, or even different interpretations of the same data can result to contradicting information in the end.

Often defenceless against unauthorised access

Some spreadsheets contain information needed by various individuals or department units in an organisation. Hence, they are often shared via email or through shared folders in a network. Now, because spreadsheets don’t normally use any access control, any user can easily open a spreadsheet file and view or modify the contents as he wishes.

Highly vulnerable to fraud

A complex spreadsheet system with zero or very minimal controls provides the perfect setting for would-be fraudsters. Hidden cells with malicious formulas and links to bogus information can go unnoticed for a long time especially if the final figures don’t deviate much from expected values.

Spreadsheet risk mitigation solutions may not suffice

Inherent complexity makes testing and logic inspection very time consuming

Deep testing can uncover possible errors hidden in spreadsheet cells and consequently mitigate risks. But spreadsheets used to support financial reporting are normally large, complex, highly-personalised and, without ample supporting documentation, understandably hard to follow.

No clear ownership of risk management responsibilities

There?s always a dilemma when an organisation starts assigning risk management responsibilities for spreadsheets. IT personnel believe users in the business side of the organisation should be responsible since they are the ones who create, edit, store, duplicate, and share the spreadsheet files. On the other hand, users believe IT should be responsible since they have always been in-charge of managing IT infrastructure, applications, and files.

To get rid of spreadsheet risks, you’ll have to get rid of spreadsheets altogether

One remedy is to have a risk management activity that involves both IT personnel and spreadsheet users. But wouldn’t you want to get rid of the complexity of having to distribute the responsibilities between the two parties instead of just one?

Learn more about Denizon’s server application solutions and how you can get rid of spreadsheet risk issues.

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Introduction to Matrix Management

A leader is responsible to empower his people and get the best out of them. Yet an organisational structure can either help or hamper performance. Worst, it can make or break success.

Looking at the fast-changing world of the global economy, whatsoever slows up and obstructs decision-making is a challenge. Hierarchical management is rather unattractive and functional silos are unlikable. Instead, employees desire to create teams equipped with flexibility, cooperation and coordination.

Recognising that companies have both vertical and horizontal chains of command, the matrix model is created. The concept of this principle lies in the ability to manage the collaboration of people across various functions and achieve strategic objectives through key projects.

Consider this scenario:

Ian is a sales executive of a company. His role is to sell a new product under the supervision of a product manager. The manager is expert about the product and she is accountable to coordinate the people across the organisation, making sure the product is achieved.

Moreover, Ian also reports to the sales manager who oversees his overall performance, monitors his pay and benefits and guides his personal development.

Complicated it may seem but this set-up is common to companies that seek to maximise the effect of expert product managers, without compromising the function of the staffing overhead in control of the organisation. This is a successful approach to management known as Matrix Management.

Matrix Management Defined

Matrix management is a type of organisational management wherein employees of similar skills are shared for work assignments. Simply stated, it is a structure in which the workforce reports to multiple managers of different roles.

For example, a team of engineers work under the supervision of their department head, which is the engineering manager. However, the same people from the engineering department may be assigned to other projects where they report to the project manager. Thus, while working on a designated project, each engineer has to work under various managers to accomplish the job.

Historical Background

Although some critics say that matrix management was first adopted in the Second World War, its origins can be traced more reliably to the US space programme of the 1960’s when President Kennedy has drawn his vision of putting a man on the moon. In order to accomplish the objective, NASA revolutionised its approach on the project leading to the consequent birth of ?matrix organisation?. This strategic method facilitated the energy, creativity and decision-making to triumph the grand vision.

In the 1970’s, matrix organisation received huge attention as the only new form of organisation in the twentieth century. In fact it was applied by Digital Equipment, Xerox, and Citibank. Despite its initial success, the enthusiasm of corporations with regards to matrix organisation declined in the 1980’s, largely because it was complex.

Furthermore, the drive for motivating people to work creatively and flexibly has only strengthened. And by the 1990’s, the evolution of matrix management geared towards creation and empowerment of virtual teams that focused on customer service and speedy delivery.

Although all forms of matrix has loopholes and flaws, research says that until today, matrix management is still the leading approach used by companies to achieve organisational goals.

Why Predictive Maintenance is More Profitable than Reactive Maintenance

Regular maintenance is needed to keep the equipment in your facility operating normally. All machinery has a design lifespan, and your goal is to extend this as long as possible, while maintaining optimal production levels. How you go about the maintenance matters, from routine checks to repairing the damaged component parts?all before the whole unit needs to be tossed away and a new one purchased and installed. Here, we will break down the different approaches used, and show you why more industries and businesses are turning to proactive maintenance modes as opposed to the traditional reactive approaches for their?field service operations.?

Reactive Maintenance: A wait and see game

Here, you basically wait for a problem to occur, then fix it. It’s also commonly referred to as a “Run-to-Failure” approach, where you operate the machines and systems until they break. Repairs are then carried out, restoring it to operational condition.?

At face value, it appears cost-effective, but the reality on the ground is far much different. Sure, when the equipment is new, you can expect minimal cases of maintenance. During this time, there?ll be money saved. However, as time progresses there?ll be increased wear, making reliance on a reactive maintenance approach a costly endeavour. The breakdowns are more frequent, and inconsistent as well. Unplanned expenses increase operational costs, and there will be lost productivity during the periods in which the affected machinery won’t be in operation.?

While reactive maintenance makes sense when you’re changing a faulty light bulb at home, things are more complicated when it comes to dealing with machinery in industries, or for those managing multiple residential and commercial properties. For the light bulb, it’s easier to replace it, and failure doesn’t have a ripple effect on the rest of the structures in the household. For industries, each time there is equipment failure, you end up with downtime, production can grind to a halt, and there will be increased environmental risks during equipment start-up and shutdown. If spare parts are not readily available, there will be logistical hurdles as you rush the shipping to get the component parts to the facility. Add this to overworked clients in a bit to complete the repair and to make up for lost hours and delayed customer orders.

For field service companies, more time ends up being spent. After all, there?s the need of knowing which parts needed to be attended to, where they are, and when the servicing is required. Even when you have a planned-out schedule, emergency repairs that are required will force you to immediately make changes. These ramps up the cots, affecting your operations and leading to higher bills for your client. These inconveniences have contributed to the increased reliance on?field service management platforms that leverage on data analytics and IoT to reduce the repair costs, optimise maintenance schedules, and?reduce unnecessary downtimes?for the clients.

Waiting for the machinery to break down actually shortens the lifespan of the unit, leading to more replacements being required. Since the machinery is expected to get damaged much sooner, you also need to have a large inventory of spare parts. What’s more, the damages that result will be likely to necessitate more extensive repairs that would have been needed if the machinery had not been run to failure.?

Pros of reactive maintenance

  1. Less staff required.
  2. Less time is spent on preparation.

Cons of reactive maintenance

  1. Increased downtime during machine failure.
  2. More overtime is taken up when conducting repairs.
  3. Increased expenses for purchasing and storing spare parts.?
  4. Frequent equipment replacement, driving up costs.?

This ?If it ain’t broke, don’t fix it? approach leads to hefty repair and replacement bills. A different maintenance strategy is required to minimise costs. Proactive models come into focus. Before we delve into predictive maintenance, let’s look at the preventive approach.?

Preventive Maintenance: Sticking to a timetable

Here, maintenance tasks are carried out on a planned routine?like how you change your vehicle?s engine oil after hitting a specific number of kilometres. These tasks are planned in intervals, based on specific triggers?like a period of time, or when certain thresholds are recorded by the meters. Lubrication, carrying out filter changes, and the like will result in the equipment operating more efficiently for a longer duration of time. While it doesn’t completely stop catastrophic failures from occurring, it does reduce the number of failures that occur. This translates to capital savings.??

The Middle Ground? Merits And Demerits Of Preventive Maintenance

This periodic checking is a step above the reactive maintenance, given that it increases the lifespan of the asset, and makes it more reliable. It also leads to a reduced downtime, thus positively affecting your company?s productivity. Usually, an 80/20 approach is adopted,?drawing from Pareto’s Principle. This means that by spending 80% of time and effort on planned and preventive maintenance, then reactive maintenance for those unexpected failures that pop up will only occur 20% of the time. Sure, it doesn’t always come to an exact 80/20 ratio, but it does help in directing the maintenance efforts of a company, and reducing the expenses that go into it.?

Note that there will need to be a significant investment?especially of time, in order to plan a preventive maintenance strategy, plus the preparation and delegation of tasks. However, the efforts are more cost effective than waiting for your systems and machinery to fail in order to conduct repairs. In fact, according to the US Dept. of Energy, a company can save between 12-18 % when using a preventive maintenance approach compared to reactive maintenance.

While it is better than the purely reactive approach, there are still drawbacks to this process. For instance, asset failure will still be likely to occur, and there will be the aspect of time and resource wastage when performing unneeded maintenance, especially when technicians have to travel to different sites out in the field. There is also the risk of incidental damage to machine components when the unneeded checks and repairs are being carried out, leading to extra costs being incurred.

We can now up the ante with predictive maintenance. Let’s look at what it has to offer:

Predictive Maintenance: See it before it happens

This builds on preventive maintenance, using data analytics to smooth the process, reduce wastage, and make it more cost effective. Here, the maintenance is conducted by relying on trends observed using data collected from the equipment in question, such as through vibration analysis, energy consumption, oil analysis and thermal imaging. This data is then taken through predictive algorithms that show trends and point out when the equipment will need maintenance. You get to see unhealthy trends like excessive vibration of the equipment, decreasing fuel efficiency, lubrication degradation, and their impact on your production capacities. Before the conditions breach the predetermined parameters of the equipment’s normal operating standards, the affected equipment is repaired or the damaged components replaced.??

Basically, maintenance is scheduled before operational or mechanical conditions demand it. Damage to equipment can be prevented by attending to the affected parts after observing a decrease in performance at the onset?instead of waiting for the damage to be extensive?which would have resulted in system failure. Using?data-driven?field service job management software will help you to automate your work and optimise schedules, informing you about possible future failures.

Sensors used record the condition of the equipment in real time. This information is then analysed, showing the current and future operational capabilities of the equipment. System degradation is detected quickly, and steps can be taken to rectify it before further deterioration occurs. This approach optimises operational efficiency. Firstly, it drastically reduces total equipment failure?coming close to eliminating it, extending the lifespan of the machinery and slashing replacement costs. You can have an orderly timetable for your maintenance sessions, and buy the equipment needed for the repairs. Speaking of which, this approach minimises inventory especially with regards to the spare parts, as you will be able to note the specific units needed beforehand and plan for them, instead of casting a wide net and stockpiling spare parts for repairs that may or may not be required. Repair tasks can be more accurately scheduled, minimising time wasted on unneeded maintenance.??

Preventive vs Predictive Maintenance?

How is predictive different from preventive maintenance? For starters, it bases the need for maintenance on the actual condition of the equipment, instead of a predetermined schedule. Take the oil-change on cars for instance. With the preventive model, the oil may be changed after every 5000?7500 km. Here, this change is necessitated because of the runtime. One doesn’t look at the performance capability and actual condition of the oil. It is simply changed because “it is now time to change it“. However, with the predictive maintenance approach, the car owner would ideally analyse the condition of the oil at regular intervals- looking at aspects like its lubrication properties. They would then determine if they can continue using the same oil, and extend the duration required before the next oil change, like by another 3000 kilometres. Perhaps due to the conditions in which the car had been driven, or environmental concerns, the oil may be required to be changed much sooner in order to protect the component parts with fresh new lubricant. In the long run, the car owner will make savings. The US Dept. of Energy report also shows that you get 8-12% more cost savings with the predictive approach compared to relying on preventive maintenance programs. Certainly, it is already far much more effective compared to the reactive model.?

Pros of Predictive Maintenance

  1. Increases the asset lifespan.
  2. Decreases equipment downtime.
  3. Decreases costs on spare parts and labour.
  4. Improves worker safety, which has the welcome benefit of increasing employee morale.
  5. Optimising the operation of the equipment used leads to energy savings.
  6. Increased plant reliability.

Cons of Predictive Maintenance

  1. Initial capital costs included in acquiring and setting up diagnostic equipment.
  2. Investment required in training the employees to effectively use the predictive maintenance technology adopted by the company.

The pros of this approach outweigh the cons.?Independent surveys on industrial average savings?after implementing a predictive maintenance program showed that firms eliminated asset breakdown by 70-75%, boosted production by 20-25%, and reduced maintenance costs by 25-30%. Its ROI was an average of 10 times, making it a worthy investment.

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