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.

Find out more about our Quality Assurance services in the following pages:

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New Focus on Monitoring Soil

There is nothing new about monitoring soil in arid conditions. South Africa and Israel have been doing it for decades. However climate change has increased its urgency as the world comes to terms with pressure on the food chain. Denizon decided to explore trends at the macro first world level and the micro third world one.

In America, the Coordinated National Soil Moisture Network is going ahead with plans to create a database of federal and state monitoring networks and numerical modelling techniques, with an eye on soil-moisture database integration. This is a component of the National Drought Resilience Partnership that slots into Barrack Obama?s Climate Action Plan.

This far-reaching program reaches into every corner of American life to address the twin scourges of droughts and inundation, and the agency director has called it ?probably ?… one of the most innovative inter-agency tools on the planet?. The pilot project involving remote moisture sensing and satellite observation targets Oklahoma, North Texas and surrounding areas.

Africa has similar needs but lacks America?s financial muscle. Princeton University ecohydrologist Kelly Caylor is bridging the gap in Kenya and Zambia by using cell phone technology to transmit ecodata collected by low-cost ?pulsepods?.

He deploys the pods about the size of smoke alarms to measure plants and their environment.?Aspects include soil moisture to estimate how much water they are using, and sunlight to approximate the rate of photosynthesis. Each pod holds seven to eight sensors, can operate on or above the ground, and transmits the data via sms.

While the system is working well at academic level, there is more to do before the information is useful to subsistence rural farmers living from hand to mouth. The raw data stream requires interpretation and the analysis must come through trusted channels most likely to be the government and tribal chiefs. Kelly Caylor cites the example of a sick child. The temperature reading has no use until a trusted source interprets it.

He has a vision of climate-smart agriculture where tradition gives way to global warming. He involves local farmers in his research by enrolling them when he places pods, and asking them to sms weekly weather reports to him that he correlates with the sensor data. As trust builds, he hopes to help them choose more climate-friendly crops and learn how to reallocate labour as seasons change.

Excel Spreadsheet Conversion to SQL Reports

Spreadsheets are flexible, inexpensive and easy to use. They are especially handy when it comes to beating report submission deadlines or making impromptu data computations.

Unfortunately, organisations heavy reliance on spreadsheets have made these User Developed Applications (UDA) into high-risk office tools. Simple spreadsheet errors like leaving out a negative sign or a cut-and-paste mistake have already caused million-dollar discrepancies. Also, when a fraudulent employee enters into the picture, the risks become unimaginable.
Think TransAlta’s spreadsheet cut-and-paste glitch (the company later called this a ‘simple clerical error’) which caused the energy firm a whopping $24 million loss or Fidelity’s overstatement of its earnings owing to the omission of the minus sign on the spreadsheet of a $1.3 billion net capital loss.

Denizon can convert your Excel Spreadsheets to a web based SQL Server Reporting Services (SSRS). It does not import Excel data, rather it allows the creation and deployment of reports in a more efficient manner by querying the data.

So what is the problem with Spreadsheets?

  • Plagued with risk issues and vulnerable to fraud
  • Lacking in control features especially when copied, edited and emailed between many users
  • A burden to regulation compliance e.g. SOX (Sarbanes-Oxley)
Moreover:
  • 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
  • Possibility of the user working on the wrong version
  • Prone to inconsistent company-wide reporting
  • Often ‘defenceless’ against unauthorised access

See Top 10 Disadvantages of Spreadsheets

What makes SQL Server Reporting Services better than Spreadsheets?

  • Free from spreadsheet risks & equipped with built-in controls that substantially reduce risks to data
  • Less prone to fraud
  • More suitable for regulatory compliance e.g. SOX
  • Designed for an agile business environment

Automatic consolidation eliminates errors and wasted time caused by tedious copy-pasting of data and linking of cells
Better collaboration capabilities allows team members to bring their heads together for planning, budgeting, and reporting even while on the go
Mobility support enables users to input data or retrieve information through their wireless mobile device

Superior sharing features ensures that everyone is exactly on the same page and viewing real-time information
Dashboards provide insightful information at-a-glance through KPIs, graphs, and various metrics
Drill-downs enable users to investigate unusual figures and gain a better understanding of the details that contribute to the big picture
Easy to learn interfaces allow your organisation to cope with fast personnel turnaround or Mergers & Acquisitions

Don’t know how to shift from Spreadsheets to SQL Server Reporting Services?

We’ve got the knowledge and expertise to assist you in:

  • Making a smooth and cost-efficient transition from risky spreadsheets to reliable reports
  • Designing and implementing SOX-compliant report-generating methods and procedures
  • Putting exposure to high-risk reporting methods a thing of the past
The Connection between Big Data and MDM

Master Data is information that is critical to your business. This could include contracts, proprietary information, intellectual capital and a whole lot more besides. Because this often reposes in a variety of different places, you need a master data management / MDM policy to control it. That way, you can link it all together in a single, secure, backed up file.

This Sounds Like Big Data

Not necessarily: big data refers to extremely large data sets that are best stored and analysed on a cloud using big technology, in order to uncover trends, patterns and associations often relating to human behaviour. Of course, if you run a niche restaurant your critical master data might be limited to a few recipes and the books you do not care to show your accountant.

The distinction is largely a question of size: think of your master data as the subset of big data that you already have your mind around. According to John Case of IBM this is probably already in a structured format and available to share. He goes on to present a cogent case for using this as a peg point around which to systematise the rest. This is because the average organisation already has master data recording customers? and prospects? behaviour.

Do I Still Need My Master Data?

Yes you do, because real people created it with the benefit of human insight. Retain it as a separate set. Then compare it with the results of big data processing for even richer insights. Two heads are better that one and that goes for data processing too.

Trends in CRM Big Data

Adding data via location-aware devices like smartphones and tablets is adding a new dimension to customer information. We now know where they were when they made the enquiry or punched in the information. Use this geo-location data to hone the way you interact with customers and service their accounts. Do not phone a customer who makes decisions at work when they are at home.

Does My Master Data Belong on a Cloud?

There are a number of ?ifs? to consider. How comfortable are you with your service provider. What would happen if someone hacked their server? There are many advantages to cloud technology. Denizon knows of solutions you can rely on, and makes sure its clients have contingency plans to protect them at all times.

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