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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Could Kanban Be?Best for Knowledge Workers?

Knowledge Workers include academics, accountants, architects, doctors, engineers, lawyers, software engineers, scientists and anybody else whose job it is to think for a living. They are usually independent-minded people who do not appreciate project managers dishing out detailed orders. Kanban project management resolves this by letting them choose the next task themselves.

The word ?Kanban? comes from a Japanese word meaning ?billboard? or ?signboard?. Before going into more detail how this works let’s first examine how Japanese beliefs of collaboration, communication, courage, focus on value, respect for people and a holistic approach to change fit into the picture.

The Four Spokes Leading to the Kanban Hub

  1. Visualise the Workflow ?You cannot improve what you cannot see. The first step involves team members reducing a project to individual stages and posting these on a noticeboard.
  2. Create Batches ? These stages are further reduced to individual tasks or batches that are achievable within a working day or shift. More is achievable when we do not have to pick up where we left off the previous day.
  3. Choose a Leader the Team Respects – Without leadership, a group of people produces chaotic results. To replace this with significant value they need a leader, and especially a leader they can willingly follow.
  4. Learn and Improve Constantly ? Kaizen or continuous improvement underpins the Japanese business model, and respects that achievement is a step along the road, and not fulfilment.

The Kanban Method in Practice

Every Kanban project begins with an existing process the participants accept will benefit from continuous change. These adjustments should be incremental, not radical step-changes to avoid disrupting the stakeholders and the process. The focus is on where the greatest benefits are possible.

Anybody in the team is free to pull any batch from the queue and work on it in the spirit of collaboration and cooperation. That they do so, should not make any waves in a culture of respect for people and a holistic approach to working together. All it needs is the courage to step out of line and dream what is possible.

The Kanban Project Method ? Conclusions and Thoughts

Every engine needs some sort of fuel to make it go. The Kanban project management method needs collaboration, communication, courage, focus on value, respect for people and a holistic approach to work. This runs counter to traditional western hierarchies and probably limits its usefulness in the West.

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Directions Hadoop is Moving In

Hadoop is a data system so big it is like a virtual jumbo where your PC is a flea. One of the developers named it after his kid?s toy elephant so there is no complicated acronym to stumble over. The system is actually conceptually simple. It has loads of storage capacity and an unusual way of processing data. It does not wait for big files to report in to its software. Instead, it takes the processing system to the data.

The next question is what to do with Hadoop. Perhaps the question would be better expressed as, what can we do with a wonderful opportunity that we could not do before. Certainly, Hadoop is not for storing videos when your laptop starts complaining. The interfaces are clumsy and Hadoop belongs in the realm of large organisations that have the money. Here are two examples to illustrate the point.

Hadoop in Healthcare

In the U.S., healthcare generates more than 150 gigabytes of data annually. Within this data there are important clues that online training provider DeZyre believes could lead to these solutions:

  • Personalised cancer treatments that relate to how individual genomes cause the disease to mutate uniquely
  • Intelligent online analysis of life signs (blood pressure, heart beat, breathing) in remote children?s hospitals treating multiple victims of catastrophes
  • Mining of patient information from health records, financial status and payroll data to understand how these variables impact on patient health
  • Understanding trends in healthcare claims to empower hospitals and health insurers to increase their competitive advantages.
  • New ways to prevent health insurance fraud by correlating it with claims histories, attorney costs and call centre notes.

Hadoop in Retail

The retail industry also generates a vast amount of data, due to consumer volumes and multiple touch points in the delivery funnel. Skillspeed business trainers report the following emerging trends:

  • Tracing individual consumers along the marketing trail to determine individual patterns for different demographics and understand consumers better.
  • Obtaining access to aggregated consumer feedback regarding advertising campaigns, product launches, competitor tactics and so on.
  • Staying with individual consumers as they move through retail outlets and personalising their experience by delivering contextual messages.
  • Understanding the routes that virtual shoppers follow, and adding handy popups with useful hints and tips to encourage them on.
  • Detecting trends in consumer preferences in order to forecast next season sales and stock up or down accordingly.

Where to From Here?

Big data mining is akin to deep space research in that we are exploring fresh frontiers and discovering new worlds of information. The future is as broad as our imagination.?

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