La Carta Mundial de la Naturaleza de 1982

Quality control activities are carried out by conducting the systematic approach of the PDCA cycle. The planning step begins with either an existence of a problem involved or preventing a problem from happening in the first place. Consequently, quality control activities start with the evaluation of actual performance. Therefore, accurate information is needed to establish factual-based decisions. Zairi (1991:37) suggests the following steps for gathering such information:

 Measuring with manufacturing  Recording of measurement  Analysing the record and

 Using the analysis for feedback and corrective action

However, in practise, tools are needed to implement the above-mentioned steps. For this purpose, Ishikawa (1985:198) suggests the ―seven quality control tools‖ which according to Montgomery (1991:101) are also called the ―magnificent seven‖ to be used by everyone in the organisation. These tools are listed in the table hereunder.

Elementary Statistical Methods (the so-called Seven Tools)

1 Check sheet

2 Histogram

3 Pareto chart: The principle of vital few, trivial many

4 Stratification

5 Scatter diagram (Analysis of correlation through the determination of median; in some instances, use of binomial probability paper)

6 Graph and control chart (Shewhart control chart)

7 Cause and effect diagram (This is not precisely a statistical technique)

Table 3.2: Elementary Statistical Methods (Ishikawa, 1985:198)

The table (3.2) above shows ‗Seven Tools‘ for elementary statistical methods advocated by Ishikawa.

The seven control tools are mainly statistical and the first step when using the tools is data collection. Data are collected to assist in understanding the actual situation. Subsequently, some statistical tools can be used to organise, clearly display and analyse data collected. In effect, a corrective action should be taken accordingly. Action may be taken to adjust process as well as to evaluate product quality (Ishikawa, 1983:12).

On the other hand, the purpose of collecting data must be clear. More over, the data itself should be relevant to the identified purpose (Ozeki Asaka, 1990:115-6). Otherwise, having huge amount of data might disturb control process. Nevertheless, an overview on the seven quality control tools are presented here below:

 Check Sheet:

A check sheet is a form prepared to facilitate the recording of data in an organised and easy manner. A check sheet would state the occurrence frequency of event (quality factor) by only putting down a check mark on the form (Ozeki, Asaka, 1990:159). The diagram below (Fig 3.9) shows one type of check sheet where the horizontal line forms a quality factor and the vertical line forms frequency.

Fig. 3.9: Data Collection (Check) Sheet for Measurable Quantities (Galgano, 1994:179)

 Histogram:

Usually, there is variation between units produced by a manufacturing process. Normally, the variation pattern is difficult to be realised from mere data (Montgomery, 1991:23). Therefore, histograms display the distribution of data comparing it to specification limits. Histogram may be constructed (see Fig. 3.10 below) by dividing data range into equal relevant intervals, these intervals are written down along horizontal axis, and a bar on each intervals is made where its height represents the frequency of data within that particular interval (Ozeki, Asaka, 1990:171-179).

 Pareto Chart

Pareto chart is basically a histogram that shows the relative frequency of quality factors. Quality factors are arranged in descending order, starting by a factor, which has high frequency down to the lowest (Ozeki, Asaka, 1990:139).

Fig. 3.11: The Pareto Diagram (Galgano, 1994:183)

Pareto Chart as in diagram (Fig. 3.11) above mainly, identifies types of defects that frequently occur (Montgomery, 1991:120). An improvement plan will therefore start with a focus on that (Ishikawa, 1983:45).

 Cause and Effect Diagram

Once types of defects have been identified, the root cause of problem should be investigated (Montgomery, 1991:121). For this purpose cause and effect diagram (also called ―fishbone diagram‖ or ―Ishikawa diagram‖) can be used.

Fig. 3.12: Cause and Effect Diagram (Ishikawa, 1985:63)

The diagram (Fig. 3.12) above, has two sides, the right-hand-side forms the effect or quality characteristics. And the left-hand-side is the cause or factors that affect quality characteristics (Ishikawa, 1983:1). This diagram (Fig. 3.12) shows that there are many factors that influence an effect, therefore, management should investigate and control the root causes in order to influence the effect (Ishikawa, 1985:61-65).

 Stratification

When gathering data to be used in further analysis, it is useful to stratify data by the type of material, type of machine, time, operator, or other types to better understanding the real situation. This facilitates easy isolation of causes and problem sources (Ozeki, Asaka, 1990:179). Furthermore, stratified data can be used in other quality control tools i.e. (check sheet, histogram, control chart). The diagram (Fig 3.13a) below shows the distribution of data arranged in a histogram for a combined two-shift department. However, diagrams Fig. 3.13b and Fig. 3.13c show the data distribution for each shift separately. That, as a result, gives more information about the real situation and in turn, directs quality control activities (Galgano, 1994:184).

Fig. 3.13a: Histograms of Department Defects

Fig. 3.13b: Histograms of Fist Shift Defects

Fig. 3.13c: Histograms of Second Shift Defects

Fig. 3.13: Using Histograms to Direct Quality Control Activities (Galgano, 1994:185)

 Scatter Diagram

Scatter diagram is a step further beyond the cause and effect diagram. In fact, cause and effect diagram gives information regarding the set of causes and factors that can influence effect. However, it does not describe the relationship between cause and effect individually (Ishikawa, 1983:87). In addition, it does not expose the weight of each factor. Having a scatter diagram, explains the correlation between pairs of

factors or between cause and effect (Ozeki, Asaka, 1990:237). This diagram is of importance in facilitating the identification of the most influential factors affecting quality characteristics towards which direct control efforts should be concentrated.

Fig. 3.14: Scatter Diagram (Galgano, 1994:186)

The diagram above, (Fig 3.14) shows a scatter diagram that depicts the moderate positive relationship between temperature and defects.

 Control Chart

A control chart is mainly used to evaluate process stability (Ozeki, Asaka, 1990:205). It is a two-dimensional graph, (See Fig. 3.15 below). The horizontal one forms measurements over time, and the vertical dimension forms the values of quality characteristics.

The chart contains three parallel lines, the centre line lies on the average value of quality characteristics, and the other two ones are the upper control limit (UCL) and the lower control limit (LCL). Measures are taken over time. If values of quality characteristics lie within the two limits, generally, it is to be said that the process is stable. Otherwise, if some values lie beyond control limits, that would be an indication for an underlying potential problem. Consequently, an investigation is required to identify the source of the problem, then to eliminate the root cause so as to prevent reoccurrence (Montgomery, 1991:103).

These seven quality control tools are ―extremely powerful‖ and, as Ishikawa states, are able to resolve the ―great majority‖ of problems in companies (Galgano, 1994:187). However the outcomes of these tools are basically information that needs to be taken into account while improving process. When having such information, the tool that maybe used to consider these outcomes is a systematic approach called the feedback loop.

Juran (1989:146) established the feedback loop, (see Fig. 3.16 below) which consist of the following basic elements:

Fig. 3.16: Feedback Loop (Juran, 1989:146)

 The sensor: which follows and evaluates process outcomes.

 An umpire: who receives information about performances from sensor then compares it against standards and goals, the result of the comparison is the identification of differences between performance and goals.

 Actuator: making the changes needed on performance to conform to goals.

It is worthwhile to mention here that going through the feedback loop while conducting control activities is essential.