Narich and Social Media

As a cutting edge technology company we have two attributes in our DNA. We are early adopters, and we like to make complex problems simple for our customers. Our first interaction with a website was with a very slow Hayes Modem connected via a Telkom landline to our local Bank. It was hard to see from the slow trickle of pixels on the screen eventually turning into hard to read data that this process would take the world by storm, but it was immediately clear that if a bank balance can be called up like Granny on her Birthday, this had to be good.

As the Internet took shape around us, we then discovered e-mail. Peers in their thirties generally dismissed this as a passing fad for Nerds, despite Bill Gate's warning that "Nerds will rule the worlds" , and proudly claimed that they would or could not be seen typing their own messages. These were the same peers thirty years later that could not communicate by e-mail or Skype with their grand children now living and working in foreign lands.

The on-line explosion is still ringing in our ears, but from a one man band sitting in a spare room, I could start to compete with any other company in the world.

As we grew, we limited products that we utilise to those which strictly served customers, so we established a grotty website, mailed and not faxed customers and suppliers, and communicated with each other internally via networks, and bought the third cell phone sold in the waterfront in the first week of a new company opening up in a cubicle called Voda something.

Things rapidly became complicated as devices proliferated. PC's, laptops, PDA's, scanners, printers, ever changing cell phones, and early  shareable server space, now called the cloud, challenged our spending and thinking patterns. What was have to have versus nice to have. 

So what has all of this got to do with Social Media. Well, we used it from birth.

Early adopting some of its features though were costly and time wasting, so when on line products started to proliferate, we first wanted to see how they would help us and our customers.

Once we had our networks, communications and website (Slightly less grotty than version 1) in place, we looked into what else would help and how. This is what we decided:

As a company with colleagues and co-workers all over the country and in other countries, we thought that a Cloud based CRM (Customer Relationship Manager) would be ideal, and we found the ideal and affordable product, Workpool. This product allows everyone of us, working on any platform, to access our own and every other shared bit of data about every task we do.

We decided to move to a fully compiled and commercially enabled website based on WordPress technology which will be launched shortly. This site will incorporate full analytics, allowing us to see what you are looking for and to make sure that you get it.

MailChimp for analytics based mail campaigns. These are targeted to existing customers to keep them informed of upgrades, specials, events etc.

AnyMeeting Webinar software. Combined with TeamViewer and Skype for remote support and training.

We have established a Facebook Page where customers can chat with us and each other. Typically this is where we can talk about events or gatherings on line about any product or process related issue.

We have established a Twitter handle @Narich for those last minute updates and if you don't get those, direct SMS services from our server. So you may be looking for our offices or service centre and we can tweet or smeet (SMS) you a quick phone friendly link.

Linked in is reserved more for peer to peer discussions. We use it to post our announcements on the Narich page but more importantly if we cant solve a technical problem through normal channels, we try this. It usually gives us technically accurate, unbiased answers to complex questions. Sometimes we also answer them.

What else should we be using?

Cutting Edge Tehnology

Visit just about any manufacturing company today and while waiting at reception one often has time to read stuff company's say about themselves. Amongst the BBBEEE ratings, "Best Supplier" and other awards and mission statements, some a bit jaded now, you often find reference to this company being a leader in its field, with Cutting Edge Technology. (CET)

How come then, when you offer CET to a production manager or senior technical person, one of the first questions to be asked is: "Who else is doing this?"



So is Copy Paste the same as Cutting Edge?

Uber is cutting edge. Everyone else is copy paste.
iPhone is cutting edge.
New Zealand Rugby is cutting edge.

The best way to explore a cutting edge project is firstly to realise that it is a process that requires more than one input. As a manufacturer, you may have a very clear idea of what outcome you desire. An equipment supplier may be able to meet parts of that desire, and a system integrator completes the circle. Academics may know what has to be integrated, and appropriate engineers will know how to do it.

If you are in the happy position to have assembled the Dream and the Team, then don't wait for someone else to prove it can be done. Be secure that cutting takes effort, and if you have a running start, your competitors will always be catching up.

Customisation is always the goal when looking to rise above the herd. It not possible for everyone to do the same old same old (so-so) things and expect customers to be excited, and excited they want to be.

Purchasing managers know that an adversarial relationship with suppliers is more expensive than a more collegial approach. Suppliers will go the extra mile to make an outcome possible with a customer who is both willing to experience the odd blip on the way, as well as contribute to the costs of trial and error.

One huge advantage German manufacturers have over their competitors is small cutting edge company's working together with a University or Academic Specialist and a major manufacturer to perfect some tine part of their overall processes. For this reason we have set up "Centre of Excellence" relationships with Academics as a bridge to "Proof of Concept" trials to allow Try before you Buy experiences.

This process seems a bit slower, requires more planning, meetings, clarifying and trust all round. The results are not a tweak or gloss to an old process, but a whole new way of doing things.

Light and Spectroscopy is in the fore field of CET. If you don't understand it, get to grips with it and reap the rewards.

Comparing Colour - Best Practice

Customers frequently comment that if they compare results from one Colour Measurement Instrument to another, results differ. This could be a comparison between competitors, old and new versions of the same instrument, or measurements with the same instruments over a period of time.

While great trouble is taken by Instrument Manufacturers like Konica Minolta to obtain high levels of accuracy and reproducibility, inevitably, a comparison of the numerical values of one measurement to the next of the SAME colour will result in some discrepancies. The big question is, are these differences MEANINGFUL to the observer.

Lets clarify some assumptions:

• Colour is not a property of an Object, but the outcome of the sum of a contextual sensing experience. In simpler language, the colour only looks like it looks under the current viewing conditions. Change these conditions and the colour will appear to change.
• The Eye and the Instrument agree: Colour Sensing Science tries primarily to emulate the human sensing experience. Mostly, if we compare two colours with an instrument, and then make the same visual assessment, we should agree on basic differences like Hue and depth of shade. The problem is that in many instances, the Instrument Settings and Conditions VARY to the Human "Settings" and conditions. Additionally, our minds are agenda driven and tend to see the expected, not necessarily what actually is.
• Instruments all have the same properties: There are around 14 settings and conditions that have to be IDENTICAL to obtain identical numeric values. Any change to a single condition changes an input to the sensing algorithm resulting in a changed output. In practice, most Instruments DIFFER in settings to have some specific market or application benefit.
• Colour can only appear to look the same if the same Colourant's are used. NOT SO. The Chromophoric Chemical Properties may derive from different chemistry meaning that at a certain wavelength colours may be identical, but at another wavelength not.
• Using Colour Space data is the most accurate representation of a colour mathematically: In reality, L*a*b values, to mention but one of a number of colour space algorithms give a hint of the colour like a GPS navigation system. It is fairly accurate, like a Street Number. In comparison Colour Cards are like Postal Codes and only offer an estimate of a colour, some even being as weak as just finding the District! To really describe a colour, a Full Spectral Reflection Curve from a Spectrophotometer As opposed the Lab values from a  Colorimeter)

• The above example of a full Visible Light Spectrum from 400nm to 700nm clearly shows precisely which spectra reflect at each nm step. Comparing CURVES is more accurate than say Lab or L*C*h as not only the outcome, but also the full journey to the colour is tracked. This is more like a finger print, and is useful say in food to differentiate between "Legal" and "Illegal" food colourant's that may look the same under a standard set of conditions, but have very different journeys to that colour. The diagram below demonstrates this well.

• Colour A and Colour C will look similar at around 450nm where they cross, and colour C and B around 570nm where they cross.
• For typical Quality Assurance though, the Delta L*a*b Colour Difference calculation is usually sufficient. You don't have all the detail, but sufficient to know how FAR or CLOSE the TARGET and SAMPLES are to make a commercial judgement.

• Visually represented as:

So if we look at just the numerical values over a long period of time without managing the context, the results are practically meaningless. Say the L values differs by 0.2. What does that mean? Can you "See" it? Does the appearance change? Quality managers love numbers, but when it come to colour, learn to love colour DIFFERENCE numbers.

 

An L value difference, averaged with an *a and *b value difference plot a better description of how far or close the colours are, and if the actual differences are see able or not. A tolerance can be set with this process, as well as a sorting process that makes visual sense.

Images supplied by Konica Minolta Sensing

Safety in Colour

Ten days (And nights) deep in the Botswana Bush heightens the senses as the battle for survival shifts to more fundamental issues like eat or be eaten. Its times like this that highlight the advantages man has over animals biologically, one of the most important being the ability to see in colour. Both animals and man respond well to movement, but mans ability to also finely discern one colour from another offers a distinct advantage.

Humans are able to see very fine shades of green from drab olives to pale lime. This helps us spot a predator in the day with ease, but helps less in the dark especially if there is no moon. While camouflage breaks up the human shape, colour discernment is a key factor in our survival outdoors, to such an extent that our sense of smell is demoted to a back up third sense after hearing. 

Still in the bush, its not wise to wear bright white, especially those nicely optically brightened garments that look cool at a trendy night spot, but wave a challenge in the face of predators, or at very least scare of the more timid types. At the other extreme, I have experienced that downside of driving a black car. During the day in Kruger Park, while slowly coasting along looking for game, a large bird all but flew into the windscreen. Apart from it being an extra 10-15 degrees hotter in the car (Without aircon) I put it down to a bird brain mentality. It was only when shortly afterwards that a large bull elephant nearly walked "Through" our car did I realise the basics of colour physics in action. The Bull may have sensed our movement, but as we were all black, he basically "Saw:" a hole or shadow in the road ahead, and continued boldly on. Mutual surprise, followed by mutual trumpeting in and outside the car, and thankfully zippy acceleration, got us out of a hot spot.

Rescue workers on the other hand will always tell you to wave something white, yellow or bright red to be noticed at sea, in the bush, on a mountain or anywhere else in the wild. There are many tales that a chance glimpse of a colour out of the ordinary helped to save a lost person.

We now see a proliferation of Hazard and Safety gear from stripes on your Nikes to Yellow jackets worn by Police. Even the ragged car guard seems to grow some authority when wearing a Haz jacket.

Next time you are choosing a Fashion Colour, think where you may end up wearing it, and decide if it will be good to be seen, or ghide!

The Power of Training

Nearly all of our support requests from customers have been covered in the initial installation and implementation training. Like sport, the phrase "Use it or lose it" also applies and I have a lot of sympathy for lab staff who are moved around from task to task without having time to either bed down their own knowledge, or share it with other colleagues.

Surveys show that in Southern Africa, and probably for the North as well, managers complain most about having unskilled staff. At the same time, there seems to be a "Grudge Purchase" attitude towards purchasing adequate training.

Things move too fast and change too often expect technical staff to just be able to pick up new software, instruments and technologies as they go along. In any case, sufficient time is never available for learning.

We make it a point in our business to trace users regularly and see if our installed systems are still up and running, and all too often we have to implement a rescue plan.

Apart from typical user skills not being taught in the first place, IT plays a fairly disruptive role in the smooth operation of systems. Firstly, there is the dreaded upgrade. Whenever software and hardware changes are made, we can be sure that system First Aid will be required. Often these upgrades are carried out without any consultation regarding their implications or impact on Laboratory Staff productivity.

Secondly, the rapid staff turnover or change. Often, a key person trained on site leaves shortly afterwards, and even if its temporary like Maternity Leave, it is usually 100% Disruptive.

Laboratory mergers, moves to new sites and simple cuts are also responsible for extremely stressed conditions. Another danger area is senior managers who insist on being trained, but who never actually put hands on the equipment later. They seldom have or take the time to pass down the required knowledge to ensure their whole user team is capable of carrying out the required tasks.

Another huge issue is time. To schedule a training visit takes more time than the training itself.

So what to do?

1. Take training offers whether free or reasonably priced as often as possible.
2. Budget training time as well as funds
3. Appoint a responsible person to deliver a result, not man a station
4. Allow Laboratory Staff a decent internet connection. The IT guys can monitor it for abuse, but don't limit the user too much, they must be free to look up terms and definitions, or joining supplier websites for Webinars.
5. Why not actually encourage reading a manual? These days they are very well written and usually cover all the FAQ's. When supplied in PDF form, they are also word searchable, which also saves time.

Before you over promote and over task a technical staff member, count the cost of their inability to actually manage the tasks that you have specified.

We invite you to take part in our training options, webinars etc.

What is the value of colour measurement?

Accurate colour measurement, or any light based test for that matter, is a lot cheaper than many traditional testing methods, particularly as its non destructive. It is however not free. So when is colour measurement essential?

Lets take a typical Industrial Example - Auto manufacturing - Quality

Car makers tend to have very high standards, obtain parts from many different suppliers around the world, made of multiple materials with varying functionality. It is not possible to start matching doors to bodies, bumpers to bonnets and other accessories like plastic wheel trims and petrol caps on the assembly line. One of the many technical specifications include a colour specification. To be accurate and universal, the specification include about 14 rules to ensure that the different parts match well under various conditions. The cost of using Spectrophotometers far outways reprocessing of cars on the assembly line, as well as the possibility of a reduced quality perception by customers. The same approach also applies to the colour of the tail lights, the intensity of the headlamps and dashboard icon clarity. 

Example - Fashion Plastics - Branding and Formulation

Fast Moving Consumer Goods (FMCG's) run to very tight time constraints. Lets say a well known brand name is going to launch a new skin care product for a high selling season like Christmas. It can take plastic container manufacturers months to get the packaging approved working visually with physical samples.

Today, a designer can post a master colour on line, and by using a Spectrophotometer with Colour Prediction Software actually formulate the plastic colour within days. Packaging, either paper or plastic, can be married to all the related media according to master colour details. This results in lots of savings as well.

Example - Textiles - Matching Fabrics - Quality

Fashion is created at high speed and the market reacts very rapidly as well. While some garments might be OK with it, mostly we would like the left sleeve or leg to match the right sleeve or leg, even when these come from different rolls of fabric, maybe over months of delivery. Spectrophotometric's make this easy, speeding up fashion and eliminating defects.

Ask us about your application

What is Colour Difference Measurement

What are we actually doing when we measure colour? To understand this, we need to understand what our actual objective is:

• Compare one colour to another
• Obtain actual colour data 
• Predict a colour formulation
  
  This post will deal with the first task only.

Compare one colour to another

Colour Comparison is usually the first and simplest task to carry out.

There are many reasons WHY we want to compare colours, like batch to batch colour continuity, quality control or to ensure one part of an assembly matches another, say in the auto industry. Colour Comparison can also be useful for Color Grading like with Flour, Fruits and Fruit Juices etc.

We have done this visually since the first time colour continuity was important. Perhaps an ancient potter or carpet weaver saw this need.

As soon as we compare colour visually, we run into a number of problems. The first is, do two people agree on the comparison, due to possible colour perception defects in one or the other observer. The next problem is, the colour seems to change at different times of day, in different physical settings. Following from this, are two observers able to agree (An opinion) on a colour. Often a supplier and a customer have different expectations which "Colour" their opinions. (Seeing red as the saying goes!)

It soon becomes clear that we need a stable reliable device that can "See" colours like humans do, and relate the data without any judgement or opinion. Enter the Spectrophotometer or Chroma meter (Colorimeter).

Studies into HOW we perceive colour reveal that the perception (In the brain) is influenced by a number of factors:

• Illuminant Source (natural, artificial)
• Size of object
• Angle of observation
• Amount of data observed
• Proximity of the object to other objects of other colours

There are about 14 "Contextual" influences on colour perception comparison, which will be dealt with in more detail in future posts, but the conclusion is that the perception of colour varies, and can not be said to be a property of an object like say weight or dimensions, but are subject to the Contextual Conditions" under which the observation was made.

To this end, the CIE (International Commission on Illumination) an international body regulating standards, prescribe the various contextual specifications in detail.

In this post, let us assume that we are comparing two colours using one CIE certificated Spectrophotometer with a known setup and using a known CIE approved Colour Space Equation (Say L*a*b)

• Prepare an object for measurement
• Measure the object
• The instrument will return L*a*b values.

These values are almost meaningless to the observer, as it is very difficult to envisage what could has been measured from the values returned. In many cases however, Quality Assurance people who are number fixated WILL look at this number, and then compare it to a "Correct" number on record. IF (Huge IF) the values were obtained UNDER THE SAME CONTEXTUAL CONDITIONS, you may infer that the numbers are close or far, but what does the difference between one number and another visually mean? If you think you will get the same numbers measurement to measurement, its a fantasy. Thats not how this works.

The quick solution to Number Madness is to use a "Target" and "Sample" approach.

A Target will be the master colour you wish to achieve, and the Sample colour will be the current batch etc.

If you measure BOTH the Target (Known wanted colour) and the Sample at the same time under the same contextual settings, you can then expect to have some sane method of comparison. The CIE L*a*b standard also come with a Colour Difference equation known as Delta ( ∆ ) L*a*b.

If you set the Instrument or software to give a Colour Difference reading, you can then see what the implication of the differences may be.

So L =  Darkness (Black = 0) or Whiteness (White = 100)

   *a  =  Redness in the + side or Greenness in the - side. The numbers indicate the INTENSITY of redness    
            or greenness.

   *b =   Yellowness on the + side and Blueness on the - side, and the numbers the intensity as for *a

By comparing the DIFFERENCE between a Target and Sample, and by reducing the difference to an AVERAGE of the difference of Target to Sample you will end up with a single value say ∆ 1.5 . This is now a meaningful number. For instance a difference of 3 is clearly visible to the human eye, and 0.5 is hard to tell.

Future Posts will cover more detail, and you can looke now at the advanced information here