Introduction: The present work was devoted to assess the awareness and usage of quality control tools with the emphasis on statistical process control in Ethiopian manufacturing industries. Semi structured questionnaire has been employed to executive and technical managers of manufacturing industries of various size and specialism across the country. Stratified random sample method by region was used to select sample industries for the study. The samples used for this study are industries mainly from Oromiya, Addis Ababa, Tigray, Amara, SNNP and Diredawa regions proportional to their size of the available industries. Methods: Exploratory method and descriptive statistics was used for data analysis. Available documents and reports related to quality control policy of the selected companies were investigated. Results and Discussions: The number of manufacturing industries involved in this study was 44. Of the sampled manufacturing industries about 60% are from Oromiya and Addis Ababa regions. It has been reported that 100% of the respondents said that the importance of quality control tools is very important to their organizations’ productivity and quality improvement (Figure 3). Quality control professionals were also asked the extent to which quality control system is working in their industry and majority of the respondents (45%) have indicated that quality control system is working to some extent in their respective industries (Figure 18). Conclusions and Recommendations: Most of the quality department of the industries did not fully recognize the importance of statistical process control as quality control tools. This is mainly due to lack of awareness and motivation of the top managements, shortage of man power in the area, and others together would make it difficult to apply quality control tools in their organization. In general, the industries in Ethiopia are deficient in vigor and found to be stagnant hence less exposed to a highly competitive market and don’t adopt the latest quality control techniques in order to gain knowledge about systems to improve quality and operational performance. We conclude that quality management system has to be established as an independent entity with a real power and hence the quality control department which is responsible for quality can make an irreversible decision with respect to quality of any given product. Moreover, the concerned bodies (government and ministry of industries) should give attention and work together with universities to ensure how these statistical process control techniques could be incorporated in a curriculum of the universities at higher levels in degree and masters programs. Furthermore, different trainings which could improve quality and efficiency of their respective management system should be given as short and long term to the employees including top and middle managers found in various industries relevant to their process.
As stated by Garvin in 1987 quality of a product is by and large considered as the aptitude of a stiff to endow with products that gratify the customer and the market [
Now days the conception of controlling and improving quality of a product has become as crucial business approach in many institutions. This approach can delight customers and take over its competitors through improving and controlling quality [
Quality is not a one-time effort phenomenon. In order to survive and win global competition, continuous effort for quality improvement is necessary. In this contemporary world, there is an increasing speed and complication of business environments hence organizations should continuously improve their processes [
Continuous improvement (CI) is a philosophy that Deming described simply as consisting of “Improvement initiatives that increase successes and reduce failures” [
The common CI methodologies are lean manufacturing, six sigma, the balanced scorecard, and lean six sigma [
More recently, six-sigma began to gain popularity in the USA in 1986, when Motorola Inc. introduced it as a means of measuring process quality using statistical process control. Six-sigma has been defined as an organized and systematic method for strategic process improvement and new product and service development that relies on statistical methods and the scientific method to make dramatic reductions in the customer defined defect rates [
A balanced scorecard is another methodology for CI generally used to clarify and update the business strategy, link the objectives of the organization to the annual budgets, allow organizational change, and increase the understanding of the company vision and mission statements across the organization. A balanced scorecard can be used to translate an organization’s mission and vision statements into a broad set of objectives and performance measures that can be quantified and appraised, and measures whether management is achieving desired results [
To overcome the weaknesses of one program or another, more recently, a number of companies have merged different CI initiatives together, resulting in a combined CI program that is more far reaching than any one individually. Lean six-sigma is the most well-known hybrid methodology, a combination of six sigma and lean manufacturing.
Maintaining Quality in manufacturing requires the practice of quality control to reduce variability in quality characteristics of the product. Since variability can only be described in statistical terms, statistical methods play a central role in quality improvement efforts. Statistical Process Control is a scientific, data-driven methodology for quality analysis and improvement [
Walter Shewhart, at the Bell Telephone Laboratories, introduced the control chart in the 1920s to distinguish between inherent or normal variability [
Common causes are problems inherent in the manufacturing system as a whole which are natural and expected. Processes that exhibit only common cause variation are said to be stable, predictable, and in statistical control. The process is said to be in statistical control when the special causes have been identified and eliminated. Shewhart charts can be used to monitor the process for the occurrence of special causes and to measure and reduce the effects of common causes [
The business lesson of the 1980’s was that Japanese firms, in their quest for global competitiveness, demonstrated a greater commitment to the philosophy of continuous improvement known as Kaizen management philosophy. Kaizen means continuous improvement involving everyone in the organization from top management, to managers then to supervisors, and to workers. It is using common sense and is both a rigorous, scientific method using statistical quality control and an adaptive framework of organizational values and beliefs that keeps workers and management focused on zero defects [
If a product is to meet or exceed customer expectations, generally it should be produced by a process that is stable or repeatable. More precisely, the process must be capable of operating with little variability around the target or nominal dimensions of the product’s quality characteristics. Statistical process control methods extend the use of descriptive statistics to monitor the quality of the product and process. Using statistical process control we want to determine the amount of variation that is common or normal. Then we monitor the production process to make sure production stays within this normal range. That is, we want to make sure the process is in a state of control. The most commonly used tool for monitoring the production process is a control chart. Different types of control charts are used to monitor different aspects of the production process. A control chart (also called process chart or quality control chart) is a graph that shows whether a sample of data falls within the common or normal range of variation.
A control chart has upper and lower control limits that separate common from assignable causes of variation. We say that a process is out of control when a plot of data reveals that one or more samples fall outside the control limits.
Statistical process control (SPC) (see
Manufacturing industry in Ethiopia is at its infant stage [
investors. Several strategies are indicated in the GTP to enable medium and large-scale manufacturing industries create competitive national economy by ensuring rapid and sustainable technological transfer, be export oriented and create a conducive environment for micro and small enterprises and agricultural developments. The strategies include attracting foreign investors to increase their investment in key industries by giving them all round and effective support, encourage industries which produce goods for the export market and substitute imports by giving them priority in accessing credit and other incentives [
To increase the pool of adequately trained human resources for industries, the GTP indicated that focus will be placed on higher education and TVET to supply manpower equipped with knowledge and skill required by manufacturing industries. The research institutes will be strengthened to support the productivity of manufacturing industries. To this end, several promising measures are taken so far such as the 70 - 30 education policy, strengthening the capacity of Science & Technology Universities, establishing several specialized research institutes including Textile institute, Leather institute, Ethiopian Kaizen institute etc.
As a result of the enabling environment created for manufacturing industry, the sector has already started attracting considerable investors and it is expected to continually attract both local and foreign investors. However, as emerging and inexperienced sector the issues of productivity, efficiency, competitiveness and quality will be challenges to the industry. In this regard, this work will investigate the experience and awareness of the manufacturing industries in quality control methods with emphasis to statistical process control tools.
The emerging Ethiopian manufacturing industry sector is believed to face competitive environment for global market. In this regard, this study has evaluated the awareness and usage of quality control tools in the manufacturing industry and provides recommendations in fostering usage of quality improvement tools in the sector. The policy makers, manufacturing industries, the University and the country at large are beneficiaries of this study. This study hence would help to recommend policy directions so as to foster quality control tools such as SPC to be applied in manufacturing industries. Consequently, this could improve industries’ competitiveness in the global market.
We believe that there is a gap on awareness and usage of quality control tools in the Ethiopian manufacturing industries with emphasis to statistical process control that should be addressed as soon as possible.
Statement of the ProblemQuality improvement is the key factor for the success and growth of any business organization.
Manufacturing industries are hence required to ensure that their processes are continuously monitored and product qualities are improved in order to survive and be able to provide customers with good products. However, the emerging Ethiopian manufacturing industry sectors are believed to face competitive environment for global market. Despite the enabling environment created for manufacturing industries in Ethiopia, as emerging and inexperienced sector the issues of productivity, efficiency, competitiveness and quality will be challenges to the industries. In this regard, this work has investigated the awareness and experience of the manufacturing industries in applying quality control tools with emphasis to statistical process control. In fact, we do believe that there is a gap on awareness and usage of quality control tools in the Ethiopian manufacturing industries. Hence, this study on the basis of empirical evidence would help to recommend policy directions so as to foster quality control tools such as SPC to be applied in manufacturing industries relevant to their processes.
To assess the awareness and usage of quality control tools with the emphasis on statistical process control in Ethiopian manufacturing industries.
The specific objectives are to:
・ assess awareness of the industries to quality control tools with emphasis to SPC:
・ determine the extent to which the producers are applying the techniques of SPC within their routine manufacturing operations:
・ identify the most common techniques used, the scope of usage, and sources of information used in setting up the systems:
・ identify constrains for applying quality tools such as SPC and
・ recommend solutions to the constraints for applying quality tools.
To acquired data on the nature and extent of quality control tools usage such as SPC among Ethiopian manufacturing industries, semi structured questionnaire method was employed to executive and technical managers of manufacturing industries of various size and specialism across the country. Available documents and reports related to quality control policy of the selected companies have been investigated. Hence, different manufacturing industries was considered from Tigray, Amhara, Oromiya, Southern nation, nationalities and people’s region, Addis Ababa and Dire-dawa.
Semi-structured questionnaire, with follow-up interviews, was conducted on a sample of manufacturing industries of various size and specialism across the country. The Questionnaire addressed awareness, usage and experience of the manufacturing industries on quality control tools such as SPC methods as well as constraints/challenges of industries for introducing quality control tools. This work relies on qualitative methods to collect and compile the empirical evidence. It was based on in-depth interviews with the company executives and/or quality control directors and internal company’s documents were scrutinized. Stratified random sample method by region was used to select sample of industries for the study. Regional sample size was considered to ensure the proportionality of the total amount of industries in the respective region. Exploratory method and descriptive statistics was employed for data analysis.
The number of manufacturing industries involved in this study was 44 and yielding a response rate of 90%. The industries that responded to the study varied in products and size. Of the sampled manufacturing industries about 59.1% are from Oromiya and Addis Ababa regions together (
Serial No. | Type of Industry | Percentage |
---|---|---|
1 | Food and beverages | 31.81% |
2 | Garment and Textile | 31.81 |
3 | Metals and Engineering | 25% |
4 | Cement | 4.5% |
5 | Others | 6.8% |
S. No. | Number of Employees Category | Percent |
---|---|---|
1 | 51 - 250 | 22.7 |
2 | 251 - 500 | 31.8 |
3 | 501 - 1000 | 18.2 |
4 | More than 1000 | 22.7 |
5 | Missing | 4.5 |
Total | Total | 100 |
Despite the enabling environment created for manufacturing industries in Ethiopia, as emerging and inexperienced sector the issues of productivity, efficiency, competitiveness and quality will be challenges to the industries. In this regard, this work has investigated the awareness and experience of the manufacturing industry in quality control methods with emphasis to statistical process control tools. Hence, due to the importance of quality control tools in industries, the term quality awareness was used to determine the number of organizations which are aware of these practices. Awareness is the state or ability to perceive, to feel, or to be conscious of events, objects or sensory patterns.
In line with this,
This study also attempted to determine how often awareness training is given regarding quality control tools to improve the quality of the products produced by their respective industries. Hence, the responses indicated that 48% of the industries are usually receiving awareness training on quality control tools, 39% of the respondents have reported that as they received on some times and about 14 % were receiving on rarely basis (
Moreover, this study has covered more questions related to awareness and usage of quality control tools. These questions can be listed but not limited to these issues:
・ Is there any department working on quality control system (QCS) in your industry?
・ How QCS is organized in your industry?
・ Do you have specific QC instruments or systems?
・ QC methods in your organization are practiced on? (that is input materials, output and/or products, at all levels of the process)
・ To what extent do you think QCS is working in your industry?
・ Challenges for using QC tools
・ How long training opportunity is given for quality control professionals?
・ QC training opportunity if any is given, where?
・ How far do you think that QC practice helps your industry to be productive?
・ The QC systems implemented in our organization are designed by?
・ Is there any Research department working on productivity, quality and profitability of your organization?
・ Do you have experience in using statistical methods as QC mechanism?
・ Do you think that the quality control department fully recognizes the importance of SPC as QC tools?
This study has also made an effort to assess whether there exist any department working on quality control system and how quality control system is organized in their respective industries. Accordingly, the responses indicated that more than three forth of the industries (88%) have established a department working on quality control system and similarly 68% of the industries have noted that the quality control system were organized by department, 27% of the industries were organized across different departments and 5% of the industries were organized at expert level (
Furthermore, the responses indicated that 86% of the industries have reported that they do have specific quality control instruments with their respective industries (
Manufacturing industries have also been asked to determine the level of awareness on how quality control methods used to practice with regard to their procedures. Of the respondents about 95.5% have noted that quality control methods are practiced at all levels starting from the raw materials and about 4.5% of the industries have experience to practice on finished products (
Furthermore, this study was also interested to know that who designed the quality control system implemented in your organization. Majority of the respondents (35.9%)
have indicated that the quality control system was designed by expatriates (
Quality control tool may be described as a method which has a clear role and defined
application; it is often limited in its focus and can be and usually is used on its own (e.g., fish-bone diagram). For this several questions were asked to organization. First was awareness of SPC and second was usage of statistical process control (SPC). This study revealed that majorities of the respondents didn’t have experience in using statistical methods as quality control mechanism (
quality department of the industries did not fully recognize the importance of statistical process control as quality control tools (
Respondents were also asked if any training is given concerning SPC. Majority of the respondents (61.4%) have indicated that they did not get any training concerning SPC (
Quality control professionals were asked to what extent that quality control system is working in their industry. Accordingly, majority of the respondents (54.5%) have indicated that quality control system is working to some extent in their respective industries (
Furthermore, most of the respondents (93.2%) have indicated they want to get training on statistical process control while the rest were not willing to get training on SPC (
Moreover, the Pareto chart below also used to analyze the challenges that could hinder to apply quality control tools. The chart hence discovered that 80% of the problems found almost in all industries not to apply quality control tools are mainly due to lack of awareness and motivation of top managements, shortage of skilled man power in the area, and lack of quality control tools together would make it difficult to apply quality control tools in their organization (
Al most all quality departments of the industries did not fully also recognize the importance of statistical process control as quality control tools. Majority of the respondents (62%) have indicated that they did not get any training concerning SPC. The Pareto chart below hence used to analyze the challenges that could hinder the application of statistical process control tools in their industries. The chart therefore revealed that 80% of the problems found almost in all industries not to apply statistical process control tools are mainly due to lack of awareness, shortage of skilled man power in the area, and others together would make it difficult to apply statistical process control tools in their organization (
Globalization has made manufacturing industries moving towards three major competitive grounds namely quality, cost, and responsiveness. Manufacturing industries are therefore required to ensure that their processes are continuously monitored and product qualities are improved in order to survive and be able to provide customers with good products. However, the emerging Ethiopian manufacturing industry sectors are believed to face competitive environment for global market. Despite the enabling environment created for manufacturing industries in Ethiopia, as emerging and inexperienced sector the issues of productivity, efficiency, competitiveness and quality will be challenges to the industries. In this regard, this work has investigated the awareness
and experience of the manufacturing industries in quality control tools with emphasis to statistical process control tools.
This study showed that 100% of the respondents said that the importance of quality control tools is very important to their organizations’ productivity and quality improvement (this response was the highest degree of importance asked to the respondents with respect to quality awareness they had) (
This study also attempted to determine how often awareness training is given regarding quality control tools to improve the quality of the products produced by their respective industries. Hence, the responses indicated that 48% of the industries are usually receiving awareness training on quality control tools, 39% of the respondents have reported that as they received on some times and about 14% were receiving on rarely basis (
This study has also made an effort to assess whether there exist any department working on quality control system and how quality control system is organized in their respective industries. Accordingly, the responses indicated that more than three forth of the industries (88%) have established a department working on quality control system and similarly 68% of the industries have noted that the quality control system were organized by department, 27% of the industries were organized across different departments and 5% of the industries were organized at expert level (
Furthermore, this study was also interested to know that who designed the quality control system implemented in your organization. Majority of the respondents (35.9%) have indicated that the quality control system was designed by expatriates (
Manufacturing industries have also been asked to determine the level of awareness on how quality control methods used to practice with regard to their procedures. Of the respondents about 95.5% have noted that quality control methods are practiced at all levels starting from the raw materials and about 4.5% of the industries have experience to practice on finished products (
A quality control tool may be described as a method which has a clear role and defined application; it is often limited in its focus and can be and usually is used on its own (e.g., fish-bone diagram). For this several questions were asked to the organizations. First was awareness of SPC and second was usage of statistical process control (SPC). This study revealed that majorities of the respondents didn’t have experience in using statistical methods as quality control mechanism (
Furthermore, this work relies on qualitative methods to collect and compile the empirical evidence. It was based on in-depth interviews with the company executives and/or quality control directors and internal company’s’ documents were scrutinized. This study has also pointed out that poor data management system (measurements poorly recorded during the process of production) was observed in all the sampled manufacturing industries. Information was also not shared between the different organizational structures of a company. This might affect the quality control system of the industries. Hence, there has to be a unit that is responsible for recording the measurements occurred during the process of production. If quality department is established as an independent system with a real power; the department which is responsible for quality can make an irreversible decision with respect to quality of a product. This could improve the quality control system of the industries.
Most of the quality department of the industries did not fully recognize the importance of statistical process control as quality control tools. Majority of the respondents (62%) have indicated that they did not get any training concerning SPC. This is mainly due to lack of awareness and motivation of top managements on statistical process control. Quality control professionals were also asked to what extent that quality control system is working in their industry and majority of the respondents (45%) have indicated that quality control system is working to some extent in their respective industries (
Berhe, L. and Gidey, T. (2016) Assessing the Awareness and Usage of Quality Control Tools with Emphasis to Statistical Process Control (SPC) in Ethiopian Manufacturing Industries. In- telligent Information Management, 8, 143- 169. http://dx.doi.org/10.4236/iim.2016.86011