Reducing Concrete

VariabilityNRMCA Webinar, 27/10/09

Ken Day FIE(Aust), FACI, FICT, HonCIA

Consultant Concrete Technologist

Don Bain, Tech.Director,

Maricopa RMC

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General Instructions

Attendees should mute their lines until they want to speak (*6 or mute on phone)

Do not place call on hold (music) Login problems: Call: 800 263 6317 Ask questions on the phone Type questions in the box Email for content / more information

Colin Lobo: clobo@nrmca.org Michelle Barringer: mbarringer@nrmca.org

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Overview High variability increases cost and blackens

reputations. The cost increase can be in terms of higher required average strength, imposed penalties, rejected concrete, or lost customers.

This webinar presents the techniques originated by Ken Day 30years ago, used on major structures in Australia, Singapore and Malaysia in the 1980s, and subsequently taken up by several major international producers and used, (without official endorsement), in many countries including USA.

Don Bain has used these techniques very successfully for the past ten years at Maricopa

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Cost of Prescription Concrete It is clear that the most expensive possible way of

ensuring that no sub-standard concrete is incorporated in a structure, is to specify that a mix be used which has an average strength high enough to allow for the highest variability likely to be encountered, and for any lack of precision in the specifier’s mix design ability,

Also, to impose restrictions on the ingredients that inhibit the use of ingredients for the supply of which suppliers have advantageous contracts and/or to require the use of ingredients which involve excessive transport distances.

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Greenhouse Gas Generation In addition it is becoming apparent that such

concrete involves substantially more greenhouse gas production than is normal in some other countries.

It is finally becoming recognised, even in USA, that it is easier, more effective, and more economical, to ensure that no rejectable concrete is produced by a batching plant than to ensure that no such concrete is accepted at a particular construction site, however large.

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Cost of Testing by Purchaser The cost to the purchaser of testing prescription concrete, and/or inspecting the production process to ensure compliance, is also likely to be significant.

Some years ago the New York Dept of Environmental Protection announced that it was proud to have reduced its control cost to around $5/cu yd. This would be well over double the cost of control of an Australian concrete producer.

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Inevitability of Change

It seems quite certain that, before long, the P2P transformation will take place. This will leave at a severe disadvantage both producers and specifiers who do not have the necessary skills, equipment and experience to take advantage of the change and many may not survive.

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Survival Requirements In order to be cost-competitive, and also to be

recognised as a desirable supplier, a concrete producer needs to have good control/low variability.

To achieve low variability a producer needs to obtain reliable, low variability, materials and to maintain an accurate batching facility.

It is also necessary to detect any problem and identify its cause at the earliest possible moment, both to avoid further deterioration and to minimise its effect on SD.

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Cost of Operating Effective QC To minimise the cost of achieving good QC, a

producer needs to have a system which extracts the maximum value from a given number of test results

or, if and when allowed, operates on the lowest effective testing frequency

and requires the minimum amount of staff time and competency (i.e. can be largely operated by low cost clerical staff).

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Material Cost Saving

For a rough assessment of material cost savings, consider a reduction of SD from 800psi to 300psi. This would require a change in mean strength of 1.28 x (800-300) = 640psi, requiring 50 to 80lb/cuyd extra cement. (however this assumes that the specifier is able to exactly design the mix, and in any case 800psi may not be an adequate worst case assumption).

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Pareto’s Principle

So what is the most efficient way of establishing effective QC?

Firstly you should realise that Pareto’s Principle applies. This principle says that if there are 100 or so possible causes of an event (in this case a reduced strength) it is almost certain that 2 or 3 of those causes will be responsible for well over half of the total number of occurrences

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Concentrate on Early Detection of Change and

its Causes So, while everything likely to affect quality should be set up as well as possible:

Purchasing materials from a reliable source Setting up a good batch plant Establishing a registered testing laboratory The concentration in operating the QC system

should be to discover which are the most important causes of problems. They will not necessarily be the same causes for all producers

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Multigrade,Multivariable,Cusum QC The technique I originated for this purpose

(and which is now in wide use in many countries but not yet exactly incorporated in any country’s Codes) I call MMCQC (Multigrade, Multivariable, Cusum QC) for analysing test data.

I need to explain each of these terms:

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CUSUM is short for cumulative sum. In this application it is the cumulative sum of differences between successive results and a selected target. A Cusum graph is around 2 to 3 times more sensitive at detecting change than a direct plot with Shewhart limits. This technique was first developed in UK in the 1960s and is used extensively in Europe.

If the target used is a fixed one, such as the desirable average strength, a Cusum graph will clearly show whether it is being maintained. If the target is the current average value (continuously maintained by the computer) the graph becomes a sensitive detector of change.

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CUSUM Explained

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CUSUM Explained

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MULTIVARIABLE

MULTIVARIABLE means that several graphs appear together so that changes in strength (for example) can be seen to correlate with other variables such as density (= unit weight), slump, temperature, testing error, batching errors, sand grading etc. I started using this technique in the UK, in the early 1950s (without Cusum) but, strangely, even UK have not officially adopted it.

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MULTIGRADE means arranging to plot results from more than one grade (product code) of concrete on the same graph. UK Cusum does use this to a very limited extent for closely allied products by applying conversion factors to results from the allied products. The conversion factors have to be established and checked and revised from time to time.

I originated the idea 20 years ago that if separate current average values of a parameter were maintained for each concrete product, then the differences from these current average values for all products could be accumulated into a single Cusum.

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Multigrade It is not obviously justifiable to accumulate

differences in strength from a 15,000psi product along with those from a 2,000psi product, or differences in density from normal concrete and structural lightweight products, but it has proved to be an extremely valuable technique.

Not only does it speed detection of change by getting several times as many results on the graphs but it makes setting up and operating a system very easy. Essentially it sets itself up as soon as there are two results for a product and continuously and automatically revises itself.

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THE FREE QC PROGRAM Apart from demonstrating the technique of MMCQC, a

substantial reason for writing this program was to enable anyone to use their own results to establish the best prediction of 28day strength from a 7day result. However the program does provide a better means of controlling concrete quality than ACI 214 if you think you cannot afford a commercial program.

Hopefully you have been provided with a copy of this program (which can be downloaded free of charge from my website www.kenday.id.au/ free programs). Please print this out as you will wish both to look at this and to see text on screen and I cannot put both on screen together. This is what you should have:

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Ken Day’s Free QC Program (ex www.kenday.id.au)

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Parameters Covered by System This program is far from a

complete system in that it covers only a limited number of parameters:

Date, Grade (Product Code), Grade Strength, Mean-Target, Slump, Concrete Temperature, Strength: one@ early age, one@ 7day, two@28day, cylinder densities (unit weights) and the “equivalent age” of the early result (this is the Arrhenius equivalent age which will be covered later time permitting).

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The program analyses the strength data to give:

the average and pair difference of the two 28day results; the average density (unit weight) the 7 to 28day strength gain; the 7day result as a percentage of the average 28day result; the predicted 28day result by adding the average gain to the

7day result; the predicted 28day result applying the average 7 to 28day

percentage; error in each of the last two predictions and finally the “K value” (the slope of the graph joining the

early result and the 7day strength - to be covered later, time permitting).

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On the Screen

The top two lines on the table give the mean and standard deviation of the numbers of the currently selected grade in the column below.

Above these two lines appear the “basic standard deviation” (see below) and the number of records of the grade currently highlighted in the table, along with the total number of records.

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At the top of the screen are:

A facility to have the records sorted by either grade (product code) or date order. Grade order is only used when it is desired to delete or extract a copy of a particular grade, otherwise the date option should be selected.

A facility to select a date range. Results outside the selected range are not discarded and can be recovered, they are simply ignored by the program and do not show on screen.

A facility to cause recalculation when changes have been made (although this normally happens automatically).

A facility to form the results into any number of multigrade groups. All entered product codes automatically appear in the RH column and groups can be formed and altered in the LH column.

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Selecting Groups

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At the foot of the table are 11 function keys:

Select graph variables. This enables choice of which variables are to appear, and at what scale, on both direct and Cusum plots.

The direct plot is of whichever grade is currently highlighted (the one shown at the top of the screen).

The Cusum plot is of all the grades in the currently selected group. The 7-28day gain v 7day strength graph is of the highlighted grade. This

graph is an important reason for making the program available. It allows you to see whether there is any tendency for higher 7day results to show a higher gain using your own results.

The print button prints out the full current table, topped by the Multigrade Stats.

Import Results imports a selected XL spreadsheet, providing it is in the correct format. I hope that some of you will have provided results for a demonstration.

Export Results exports an XL spreadsheet of all results. Note that this is in the format that must be used to import results.

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7-28 day strength gain v 7day strength

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Selecting Graph Variables

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The direct plot graph can be used to see whether a particular low or high result is confirmed at both 7 and 28days and if it is explained by density (= unit weight)

•, slump or temperature.

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The Cusum Graph

The Cusum graph is the real heart of the system. With all grades included, the Cusum plot involves no effort to display at the conclusion of result entry each day, and if the cusums do not show any significant change in slope, no further action is needed, although it is worthwhile, and very little extra effort, to press the Multigrade Stats key to check that no grade with very few results (and so having little effect on the graph) has developed a problem.

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Temperature effect 11-13 June

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Detecting Cause of Change If there is a change in slope, its cause should be investigated. If it is

due to a change in W/C ratio (usually, but not necessarily, due to a change in water content) then the unit weight should also be affected, since water is the lightest ingredient (other than air) and either slump or temperature is likely to provide an explanation (and confirmation). Cylinders should be weighed on receipt at the laboratory rather than at test so that a change in strength can often be anticipated before even the 7day strength is obtained.

Cusummed results over an extensive period from new clients usually show a mirror image of strength and temperature with reduced strengths during warmer weather. Where permitted to do so, existing clients know to vary cement content slightly to save expense in cooler weather and avoid problems in hotter weather, so avoiding the “mirror image effect” of temperature.

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Detecting Cause of Change It is again emphasised that there are many possible causes but that

a particular very limited number, different for different plants, are likely to recur at a particular plant.

Where the cause is detected (by density = unit wt) as being due to W/C variation, but not explained by slump or temperature, the next two possible causes to consider are batching and sand grading.

Batch plant data should in any case be frequently inspected from the viewpoint of cost and a modern plant will be able to download actual batch quantities for every batch and the better ones will automatically raise an alarm in the event of an error exceeding a pre-set value. However persistent small errors can be experienced and can amount to a significant cost if not corrected.

If time permits we will look at batch plant data analysis later. Don Bain will present this, as he has been involved in its development.

Or you can download a screencam on it from www.kenday.id.au.

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The attitude to sand data depends on the situation. Sand gradation (my Specific Surface) and silt content (by crude settling test) enables a quite precise calculation of its effect on water requirement (and the adjustment that should be made to sand percentage) which can be quite substantial. However many sand sources are reasonably consistent and sand sieve analysis is often done at low frequency and also often at an unhelpful stage for MMCQC graphing (eg samples taken at the extraction site rather during batching).

One approach is to take reasonably frequent (e.g. daily or 2 or 3 times a week) samples during batching so that they can be sieved later if no other cause of change is discovered. (this retained sample technique is also useful for cement quality, which is too expensive for frequent testing for a small producer).

Silt content is different. If it has been found to be a problem from time to time, then a continuous alert is worthwhile. Increased silt is often visually detectable. Also shaking a sample in water and allowing to stand (whether in a measuring cylinder or any old bottle) takes little time and effort.

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Sand Grading Variation

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Locating problems

Where a change of slope is not uniform, nor explained by varying slump, temperature and density, it is time to look at whether particular grades have a problem. Again, Multigrade Stats should be consulted, but if there are many results in a grade, the last few results will not necessarily bring it to the top of the table (and hopefully we are still looking at a problem before there are any 28day results from it). Shortening the date range may help, printing out Stats before and after the onset of the suspected problem.

To some extent one approach is to look at past results over a substantial period (i.e. including 28day results) to see what has caused past problems, because the same problems are the ones most likely to recur.

To look at cusums in individual grades it is necessary to nominate the grade as a group.

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Multigrade Statistics

Multigrade Stats displays a statistical analysis of all grades in the program arranged in order of departure of the mean from the required target value (but the target value in this program is based on 5% defective, so Grade Strength +1.65 x SD*).

Undelete Records allows recovery of results inadvertently deleted providing the program has not been exited.

Calculate performs all calculations. Clear calculated should delete all calculated values but

does not appear to be working.

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Multigrade Analysis Table

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Use of the system A prime objective is to display the concept of MMCQC A secondary objective is to establish that prediction of

28day results should be by adding the average 7 to 28day gain to the 7day result NOT by regarding it as a percentage.

To this end the gain graph is provided, the two predictions and prediction errors are shown, and the top line shows the average error by the two

methods. Once you are convinced of this, using your own results, a substantial part of the spreadsheet is essentially not really needed.

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7-28 day strength gain v 7day strength

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Two Estimates of Standard Deviation The system calculates two SDs (in the Multigrade

Analysis). One is traditionally calculated (as by a calculator), the other takes the average difference between successive results in the same grade and divides it by 1.13. If the results are truly normally distributed the two values should be the same.

The value of the exercise is that if there is a change in mean value during the run of results the traditional value will be increased but the basic SD will be little affected.

So this provides a simple alert as to which, if any, products have experienced a change and should be further investigated (however it uses 28day results and the cause of any problem will hopefully have been established before they are available).

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Two Estimates of Standard Deviation Deviation

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Early Age Strength (K value) The system makes provision for the entry of an early age strength

(usually less than 24 hrs but could be 3 or 4 days) which has to be accompanied by its Arrhenius Equivalent Age (see website or book) which would be read out by some temperature probes. The system then uses these values along with the 7 day strength to calculate a K value (the slope of the line joining the early strength and the 7day strength on a graph of strength v Log Equivalent Age. This value can be entered in the early age prediction system which appears elsewhere on the website but a prediction of 28day strength is not included in the system demonstrated here. This is because the purpose of the early age system is to regulate prestressing, demoulding, or de-propping rather than QC. Since it uses the 7day result to obtain the K value it would give the same prediction of 28day result at the same time. However the full Conad system uses the current average K value to give an early prediction of 28day strength

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Early Age Prediction of Strength

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K Value for early age system

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System Limitations

This little system, with less than a dozen columns of data entered (comprising only slump, temperature, density and strengths apart from sample identification) and only 8 direct and Cusum graphs, will detect real change, as opposed to an occasional low result, much earlier than standard techniques, and usually reveals the cause of more than 50% of such changes.

However it should be realised that commercial systems such as the full Conad system allow up to 40 data items and can produce more than 80 graphs, pulling in external data on materials and batch plant performance.

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Ease of Use

It might be thought that such a system would be too complicated to learn and consume too much operator time, but this is not the case. All tests carried out have to be recorded somewhere and the system simply automatically collects all recorded data and makes it available in the analysis.

As with the mini system, the (probably clerical) data entry person simply presses a button to display a multigrade graph at the conclusion of data entry and looks for a change point. The graphs displayed at this stage are probably exactly the same as the ones for the mini system. The big difference is that back-up information available to the person in charge when a change is experienced is both far more extensive and more quickly and easily available.

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Don Bain I will now hand over to Don. His contribution is very

valuable in that he has used the Conad system for10years and is able to assure you that it has improved his efficiency, reduced his problems, and saved his company a great deal of money.

He also provides valuable insights into obtaining co-operation from cement producers and external testers.

However it should be noted that his examples do not use the free program and illustrate that sometimes local factors – in his case cement variability – can have a greater effect than the water content variation I have found to predominate in most countries.

I will continue to be available for the discussion session.

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BATCHING VARIATION DOLLARSYEAR TO DATE

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DAILY CUMULATIVE BATCHING VARIATION

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ANALYSIS CRITERIASINGLE MIX – 23500LW 3500PSI

LIGHTWEIGHT

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ANALYSIS CRITERIAALL CONCRETE APRIL 1 THRU OCT 10

2009

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CONCRETE STRENGTH CUSUMINCLUDING PREDICTION

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CONCRETE STRENGTH CUSUMNO PREDICTION

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CUSUM – CONCRETE STRENGTH, SLUMPTEMPERATURE

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CUSUM GRAPH7 DAY to 28 DAY GAIN

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CUSUM GRAPH28 DAY STRENGTH vs CEMENT C3S

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CUSUM GRAPH28 DAY STRENGTH vs CEMENT C3A

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CUSUM GRAPH28 DAY STRENGTH vs CEMENT BLAINE

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Conad System Data Input (1)

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Conad System Data Input (2)

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Conad System Data Input (3)

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Record Selection

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Additional Search Criteria

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Multigrade Report Details Selection

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•Multigrade Analysis

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Graph Selection Screen (80+ items)