Metrology has been commonly seen as “cost-centre”. In this first post in the topic of “productive metrology” that is metrology as “profit-centre”, we will start by discussing the philosophical goal of metrology to gain know-how or wisdom.
This post is an opening door for further discussion. That is, metrology can bring economic benefits in a company or organisation.
Metrology is the science of any measurements. The essence of metrology is to transform raw data (obtained by any measurements) into a know-how or wisdom that can be implemented as policy or used to generate new ideas.
This premise of transforming raw data (first-hand data) into know-how is what we will discuss.
By discussing this aspect as the introduction to “productive metrology” that perceives metrology as “profit-centre”, we can build some ideas and feeling about why metrology is something that bring economic values as much as selling a product for a profit margin.
At the end of this post, readers will have a tangible feeling on how metrology can transform raw data into know-how and then into new idea, procedure, design or others.
Let’s go into the discussion!
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Transforming data into know-how/wisdom
As lord Kelvin said, “if you can’t measure it, you can’t improve it”.
From this statement, he pinpointed that metrology is key for any improvements in any disciplines, including both process and/or product.
Metrology is the key for any meaningful improvements because only with metrology, we can transform any raw data (that are not very meaningful for us) into knowledge and then know-how/wisdom.
This know-how and wisdom are the one that will give tangible benefits and can generate or propel new ideas, concepts, policies and any other decisions to improve our company or organisation or life.
Figure 1 below shows the illustration of step-by-step transformation of raw data, into information, into knowledge and then finally into know-how/wisdom.
In figure 1, the horizontal axis is the process on how to transform data. Meanwhile, the vertical axis is the purpose of the processes on transforming the data.
The first step is the raw data collection by using measurements. These measurements are conducted in a research activity. This activity is to collect the details or the quantity about something, either process or product or both.
From these measured raw data, data analyses are performed to extract any quantified information. By using this quantified information, a context and causal relationship about the data can be discovered. For example, there is a specific behaviour shown from the collected data about a process or product.
The process of measurement to collect data and data analysis to extract quantitative information is called metrology.
The productive metrology starts where we can transform this information into some quantified knowledge. This quantified knowledge is performed by investigating the causality of data into a process or product. The information is analysed as whole perspective about the process and the product.
Finally, from the quantified knowledge, a know-how or wisdom can be obtained so that a reflection can be carried out about the process or product, this know-how or wisdom can be in a form of new ideas, new product or process design, new policy and other new things.
Figure 2 below shows how metrology as the generator or enabler for raw data transformation into know-how or wisdom. In Figure 2, the transformation can be presented in a more tangible way.
That is, metrology is realised by measurements to get raw data and then analysed to get quantified information. From this quantified information, knowledge and then know-how can be developed, leading to a new idea, new concept, new design, new model, new decision or others.
A real example of the cycle illustrated in figure 2 above is as follows.
Let us imagine that we want to study and improve the process of making a bread.
Initially, we design an experiment to measure the softness of breads and the temperature at which the breads are baked. From these measurements, we get a set of temperature data and bread’s softness data.
From these data, we perform a statistical analysis, for example, an one-way ANOVA or regression analysis to find the correlation between the bread’s softness and the baking temperature.
From this analysis, we may find that the higher the temperature the less soft the bread will be.
From this statistical analysis, we can obtain a knowledge of how temperature will affect the softness of a bread.
From this quantified knowledge, we then can create a procedure on how to optimally bake a bread at the best baking temperature range.
This know-how is a type of new decision or procedures that can only be realised by productive metrology.
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An opening discussion on how metrology can be productive and hence can be perceived as “profit centre” instead of “cost centre” has been started.
Specifically, in this post, the role of metrology to transform raw data into knowledge and then finally into know-how or wisdom has been discussed.
The role of metrology as the enabler of transforming raw data into a quantified information, and then into knowledge and then finally into know-how or wisdom is the philosophical reason on why metrology is “productive”.
That is, metrology can bring economic benefits in a company or organisation.
A real tangible example has been given to elaborate the concept of raw data transformation into know-how or wisdom that is enabled by productive metrology.
 Kunzmann, H., Pfeifer, T., Schmitt, R., Schwenke, H. and Weckenmann, A., 2005. Productive metrology-adding value to manufacture. CIRP annals, 54(2), pp.155-168.
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