6.1 Introduction
The previous chapter was devoted to an analysis of the productivity of the responding companies. This chapter is an extension of the discussion in chapters four and five. It focuses on measures of quality and their effects on productivity. It begins by discussing measures of quality (scrap, rework, defects and complaints) by applying frequencies and percentages in the data set for FOC’s and LOC’s, and then examines the differences between the two groups in terms of the relationship between measures of quality and the business sector, and between measures of quality and productivity. It investigates the relationship between selected QM practices and measures of quality, and explores the differences in using QC practices and quality performance functions separately for foreign owned and locally owned Pakistani manufacturers.
6.2 Rate of scrap during production
Table 6.1 represent the frequencies and percentages of scrap produced by the responding companies. The respondents were asked to give average percentages of the products they considered as scrap during the manufacturing processes.
Table 6.1: Percentage scrap in the companies
Percentage of Scrap in the responding companies
No. Of Companies Percent (%)
Less than 1% 92 34.8
1-5% 69 26.1
5-10% 44 16.7
10-15% 36 13.6
15% or more 23 8.7
Total 264 100.0
Some 35% reported less than 1% scrap, 26% have scrap between 1-5%, 17% 5-10% scrap, 14%10-15% scrap, and 9% 15% scrap and more. The details of the
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percentage of scrap based on ownership and type of industry are discussed in sections 6.6 and 6.7 respectively.
6.3 Rate of rework during production
Rework products are completed but do not meet specification or acceptance criteria and are redeemed for fresh work or repair and reprocessing. The companies were categorized by the same percentage groupings as for scrap: 1%, 1-5%, 5-10%, 10-15%, 15% or more, as shown in table 6.2.
Table 6.2: Percentage rework in the companies
Percentage of rework in the responding companies
No. Of Companies Percent (%)
Less than 1% 63 23.6
1-5% 83 31.1
5-10% 42 15.7
10-15% 45 16.9
15% or more 34 12.7
Total 267 100.0
Sections 6.6 and 6.7 discuss the percentage of rework based on ownership and type of industry.
6.4 Rate of defects during production
This section analyses the rate of defects identified during production processes, as shown in Table 6.3, grouped as for scrap and rework.
Table 6.3: Percentage defects in the companies
Percentage of defects in
the responding
companies
No. Of
Companies
Percent (%)
Less than 1% 90 34.2
1-5% 67 25.5
5-10% 53 20.2
10-15% 40 15.2
15% or more 13 4.9
Total 263 100.0
The details of percentage of defects based on ownership and industrial sector are given in sections 6.6 and 6.7 respectively.
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6.5 Number of complaints received by the companies
The study considered the number of complaints received on monthly basis as less than 5, 5-10, 10-15 and more than 15 (see table 6.4).
Table 6.4: Number of complaints in the companies
No of complaints received complaints and 8 reported more than 15 complaints.
6.6 Measures of quality and type of ownership
This section examines the relationship between measures of quality and type of ownership of the sampled companies.
Table6.5: Cross tabulation of measures of quality (scrap, rework, & defects) with type of ownership
Measures Companies Less than 1%
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Here cross tabulation is used to find out the relationship between the variables scrap, rework, complaints and defects on one hand and type of ownership (foreign or local) on the other, as shown in tables 6.5 and 6.6 respectively. As presented in Table 6.5, 65% of foreign companies reported the percentage of scrap as less than 1%, as against only 23% of local companies. No foreign company claimed scrap rate above 10%. At the other extreme, 31% of LOC’s reported scrap rate of 10% or more.Table 6.5 cross tabulates the percentage differences between measures of quality and the nature of ownership. The evidence clearly shows that FOC’s have less scrap than do LOC’s. It was indicated in chapter four that the majority of the FOC’s had adopted QM practices, unlike locally owned companies (see section 4.3).
Similarly, FOC’s showed a higher level of commitment and active involvement in quality initiatives (see section 4.5), a more participative style of management and better training opportunities to employees (see section 4.5).That 31% of locally owned companies reported rates of scrap above 10% led the researcher to investigate the raw data for further analysis. Before this new analysis, the companies were divided into two group based on their percentage scrap rate: low scrap producing LOC’s with less than 10% scrap, and high scrap producing LOC’s of 10%
or above. The researcher randomly picked six companies from the high scrap producing group: two from the chemicals sector and four from the textile sector (see table 6.6). For comparison purposes, the same types were selected from the low scrap producing group (see table 6.6).
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Table 6.6: Comparison between high and low scrap producing LOC’s
Table 6.6 shows that, of the six high scrap companies, four had adopted only ISO 9000 QM practice, whereas the low scrap producing companies are using multiple or a wide range of quality management practices; one exception is the last textile company, which claimed to have adopted only the ISO 9000 practice.
Table 6.6 further compares local companies in terms of high scrap and low scrap production, on the basis of QM practices, productivity, and QM implementation factors such as leadership, training, management style and customer focus. The calculation of scores for QM implementation factors were made by adopting the same approach as that used in calculating productivity (see section 5.2). From the table it can be stated that high scrap producing companies have lower scores for productivity, leadership, training, management style and customer focus than do low scrap producing companies. For example, the first chemical company from the table has high scrap with a low productivity score of 6, compared to the low scrap producing chemical company with a productivity score of 19. In the same manner, the productivity score for the first high scrap textile company is 9, compared to 21 for the low scrap textile companies shown in table 6.6.This result implies that those local
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companies which effectively implemented QM elements such as leadership, training, management style and customer focus have achieved higher productivity and quality by reducing their rate of defects. Similarly, the one textile company, which adopted only ISO 9000, was in the low scrap producing group due to better implementation of QM elements. This suggests that the adoption of QM practices does not work unless the implementation process is appropriate.
In terms of cross tabulation between rework and type of ownership (see table 6.5), 48% respondents from foreign companies reported a rate of rework less than 1% as against only 14% of local manufacturing companies. Additionally, 45% foreign companies claimed rate of rework between 1-5%. The remaining five FOC’s have rate of rework between 5 to 10% in their respective companies. Similarly, 26% local companies stated rework rate between 1 to 5%, 19% responding companies reported percentage of rework between 5 to 10%. In addition, 23% LOC’s were between 10 to 15% rate of rework, and finally, 18% local companies reported rework rate of 15% or more.
Once again, the high rate of rework among most of the local companies led the researcher to look into the raw data, and the same criteria were used to categorize them according to high or low rework. The low rework producing local owned companies produces rework rate of less than 1 to 10% rework, while high rework producing local owned companies produces rework rate from 10 to more than 15%
rework. The researcher randomly picked six local owned companies from high rework producing group, two (2) from engineering sector, one food manufacturing company, and three (3) from textile sector (see table 6.7).