In the dynamic realm of construction, ensuring top-notch quality in every project is paramount. Accurate data collection stands as a cornerstone of quality control, offering invaluable insights into various project facets.

From material quality to workforce efficiency, the benefits of meticulous data collection cannot be overstated. Let’s delve into why accurate data collection is crucial for effective quality control in construction projects.

1. Precision in Decision-Making:

Data collection provides a factual foundation for decision-making. Project managers and stakeholders can analyze real-time data to make informed choices that steer the project towards success.

Whether it’s altering construction methodologies or refining resource allocation, precise decisions based on accurate data are instrumental in maintaining quality standards.

2. Early Detection and Mitigation of Issues:

Timely identification of discrepancies is key to maintaining quality. Accurate data allows for the early detection of deviations from the project’s defined standards.

This early awareness empowers project teams to address issues swiftly, reducing the potential for expensive rework and ensuring that the project adheres to the highest quality benchmarks.

3. Continuous Improvement and Optimization:

Collected data serves as a learning tool. By analyzing past projects and their respective data, construction teams can identify areas for improvement.

This iterative process aids in optimizing construction methodologies, enhancing efficiency, and ultimately elevating the quality of future projects.

The purpose of collecting data

A great deal of data are collected in construction work. Let us first consider the purpose of collecting these data. When we introduce a particular method of doing a job, it is natural that we consider whether the method is appropriate or not.

The decision is usually based on past results and experience, or perhaps on conventional methods.

However, in the case of factory work, where data are collected through the actual manufacturing process, the procedural methods are introduced on the basis of the information obtained.

The construction procedure will only be correct if a proper evaluation is made, and on-the- job data are essential for making a proper evaluation.

Since data will form the basis for action and decisions, the data which should be obtained from construction operations will vary with the construction procedure involved.

Classification of Data

We have classified these data in terms of the various purposes.

(1) Data to assist in understanding the actual situation

These data are collected to check the extent of the dispersion in part sizes coming from the machining process, or to examine the percentage of defective parts contained in lots received.

When the number of data increase, they can be arranged statistically for easier understanding.

Estimates can then be made concerning the condition of lots received and the manufacturing process, through comparison with specified figures, standard figures, target figures, etc.

(2) Data for analysis

Analytical data may be used, for example, in examining the relationship between a defect and its cause.

Data are collected by examining past results and making new tests. In this case, various statistical methods are used to obtain correct information.

(3) Data for process control

After investigating product quality, this kind of data can be used to determine whether or not the manufacturing process is normal.

Control charts are used in this evaluation and action is taken on the basis of these data.

(4) Regulating data

This is the data used, for example, as the basis for raising or lowering the temperature of an electric furnace so that a standardized temperature level may be maintained.

Actions are prescribed for each datum, and these measures must be taken accordingly.

(5) Acceptance or rejection data

This form of data is used for approving or rejecting parts and products after inspection. There are two methods – total inspection and sampling.

On the basis of the information obtained, it can be decided what to do with the parts or products.

Collection of representative data

Data serve as the basis for action. After evaluating the actual conditions, as revealed by the data, the proper action can be taken.

Thus, the most important thing to do first is to determine whether or not the data represent typical conditions.

The problem can be stated as follows:

1) Will the data gathered reveal the facts?

2) Are the data collected, analyzed and compared in such a way as to reveal the facts?

No. 1 is a problem of sampling methods;

No. 2 is a problem of statistical processing.

The most important point in sampling is to know just what the data are used for in other words, to be certain of the purpose.

For example, if the problem with a given product is impurity dispersion, it is hardly sufficient to take only one sample per day to find out the daily dispersion rate.

Or, in comparing defects produced by workers A and B, it is essential to take two separate samples from both workers’ products.

It means one must give full consideration to the reason for collecting data, proper sampling techniques, and stratification.

One should not take a disproportionate share of a certain kind of data simply because they can be collected easily.

Also, partial data which happen to be convenient to collect are not necessarily effective data.

But even the use of proper sampling techniques is not enough. It is necessary to see that the data represent the facts and that the statistical method applied is such that an objective evaluation can be made.

For example, even if you have 100 data showing the hardness of material X, it is generally impossible to draw any conclusions from the numerical value alone.

The basis for a decision can only be obtained after comparing them with the overall situation, as in a histogram or check sheet.

And, in comparing the hardness of material Y with that of material X, it is still necessary to use statistical techniques, after considering the dispersion in the samples of each.

Reminders for collecting data

Pay attention to the following when collecting data.

(1) Remember to take action according to data:

We must always remember to make data our basis of our action, otherwise they will not be collected in a positive manner. Get into the habit of discussing a problem on the basis of the data and respecting the facts as shown by them.

(2) Clarify the purpose of collecting the data

In addition to this, it is still necessary to make the purpose clear. Only then can the necessary comparisons and the kinds of data to be collected be determined. It is important to review the purpose of the data being collected and also to see if they are really being put to effective use.

(3) Remember to get everything into data

Just because the kind of data needed has been determined it does not automatically follow that such data can be collected. Lack of instruments or manpower, difficulties in quantification, etc., are common problems.

What is essential at this stage is a will and ingenuity for collecting data. The key to the solution is whether one can collect data skilfully. The difference between good and poor factory and group leaders becomes evident here. The good leaders take great pains to obtain data and often come up with unique methods.