Quality Control Measures at Benue Breweries Limited, Makurdi

Quality Control Measures at Benue Breweries Limited, Makurdi Free Online Research Papers A PROJECT WORK SUBMITTED TO THE DEPARTMENT OF PHYSICS, UNIVERSITY OF AGRICULTURE, MAKURDI, BENUE STATE, NIGERIA. IN PARTIAL FULFILLMENT OF THE AWARD OF BACHELOR OF SCIENCE DEGREE IN INDUSTRIAL PHYSICS APRIL, 2010? DECLARATION I declare that this project work is my original work and has not been previously submitted for any degree to any university or similar institution. . EGWUATU FELIX IKECHUKWU DATE CERTIFICATION This to certify that this project is an original work carried out by EGWUATU FELIX IKECHUKWU, with the registration number UE/9400/06 under the supervision of Prof, E.H. AGBA in the Department of Physics, University of Agriculture, Makurdi and meets the requirement for the award of the degree of Bachelor of Science Honors in Industrial Physics .. Prof. E.H. AGBA DATE PROJECT SUPERVISOR . Dr. A.N. AMAH DATE HEAD OF DEPARTMENT .. . EXTERNAL EXAMINER DATE DEDICATION This project work is dedicated to the Almighty God the giver of all good things, who has given me the inspiration and zeal that saw me through this programme and also to my uncle Late Mr. Ejike Callistus Okwegba who is no longer here to witness how mighty the little seed he sow has turned out to be. ACKNOWLEGEMENT I wish to express my immense gratitude to the Almighty God, the giver of all knowledge and the protector who has guided me throughout the period of my programme and has made it possible for me to successfully carry out this project. Also my profound gratitude goes to my parents Sir. Felix .N. Egwuatu and Lady Bridget Egwuatu for their fervent prayers, good parental upbringing, supports and above all for all the love they shower upon me all my life. I am also indebted to my siblings Mrs. Ogochukwu Okogba, Mrs. Chinyere Ekeh, Kenechukwu, Somtochukwu, Chukwuebuka, and Nzubechukwu Egwuatu and to my uncles and aunts Mrs. Benedette Oforah, Miss Maria Egwuatu, Mr Mrs. Richard Egwuatu, Mr Mrs. Jerome Egwuatu, late Mr Ejike Okwegba, Rev. Sr. Pat Okwegba, and to my in-law Lt. M.C. Okogba, to my nieces Uzoma and Chinwe Okogba and Omasilichukwu Ekeh and to my cousins, Ijeoma Ikala, Ekenedilichukwu, Chioma ,Chika, Chukwuma and Onyebuchi Oforah and to my best friend Jane Onwunumagha for their pra yers, care and supports. Many thanks to my H.O.D Dr. A.N. Amah, my project supervisor Prof. E.H Agba and all the lecturers in the department who with their individual efforts have helped me to achieve my goals. My appreciation goes to my mentors Late Eng. J.L.C. Ifem, Late Mr. Ephraim Akwuaka, Mrs. Akwuaka, Mrs. L.N. Tse (Ag. Registrar Uni-Agric, Makurdi) and Mrs. Asoh ( Quality control manager, bbl, Makurdi) for their efforts and supports towards my education and to my coursemates most especially Cosmas Agbo, Ejegwoya Peter Ogah (Odinga), Amuzie Chimex Tsev Terkimbi, Olusegun Ishola, Udeh Inalegwu, Davis Onojason, and Lawal Joseph. I pray that the Almighty God will reward you all accordingly. ABSTRACT The importance of quality has been long recognized in the manufacturing environment in order to obtain or manufacture higher quality products. In manufacturing environment, quality improves reliability, increases productivity and customer satisfaction. Quality in manufacturing requires the practices of quality control. This research work addresses the study on quality control in Benue Brewery Limited (bbl) makers of more lager beer. The case study involves measurement of some randomly selected finished products (more lager beer). This work focuses on result of the physical measurement of the products (volume content) from the company which were analyzed using some Statistical Quality Control tools. Included are Descriptive statistics (mean and range), Acceptance sampling and Control chart for variables (mean chart and range chart).Based on the findings of the work none of the plotted values in fig.4.1 and fig.4.2 went out of the control limits (upper and lower) rather clustered round the centre lines which shows that the production is under control and it can be said that the machines are functioning properly. ? TABLE OF CONTENT Content Page Title Page: i Declaration: ii Certification: iii Dedication; iv Acknowledgement v Abstract: vi Table of Contents: vii List of Figures: x List of Tables: xi CHAPTER ONE 1.0 INTRODUCTION 1 1.1 Background of Study: 1 1.2 Statement of the Problem: 6 1.3 Objective of the Study: 6 1.4 Significance of the Study: 7 1.5 Scope of Study: 8 CHAPTER TWO 2.0 LITERATURE REVIEW 9 2.1 Review: 9 2.2 Overview: 9 2.3 History of Quality Control: 14 2.4 Quality Assurance: 15 2.5 Statistical Quality Control: 17 2.6 Components of Quality Control: 18 2.7. Implementation of Quality Control: 20 CHAPTER THREE 3.0 METHODOLOGY 22 3.1 Method of Data Collection: 22 3.2 Method of Data Analysis: 23 3.3 Measurement of the volume content of the bottles: 28 3.4 Problems and Limitation of Data Collection: 29 CHAPTER FOUR 4.0 DATA PRESENTATION, CALCULATION AND DISCUSION 31 4.1 Data Presentation and Calculation. 31 4.2 Discussion: 47 CHAPTER FIVE 5.0 CONCLUSION AND RECOMMENDATION 49 5.1 Conclusion 49 5.2 Recommendation 50 REFERENCES: 52 LIST OF FIGURES Figure Page 2.1 Typical steps of quality control: 16 2.2 Typical steps of quality assurance 16 4.1. The Mean Control Chart: 45 4.2 The Range Chart 47 LIST OF TABLES Table Page 4.1: Raw data distribution table: 32 4.2: Mean-Range distribution table 42 CHAPTER ONE INTRODUCTION 1.1 Background of study Quality control (QC) being one of the prominent activities employed to ensure a certain level of quality in a product or service, has emerged as a prime engine and an important factor for any successful industry operating in today’s highly competitive business environment. However, the industries in the developing countries that are problem oriented in terms of competition in the market are also adopting the concepts and techniques of quality control in their various business strategies. Interestingly, businesses in Nigeria are beginning to realize the importance and adopting the concepts of quality control to achieve excellence and effectiveness in their products and services. Manufacturing industries for example are taking the lead in adopting and implementing the contemporary quality control to optimum advantage. Quality control is a topic pioneered by manufacturing sectors. Nowadays the field has developed tremendously and its techniques, tools, concepts and methodologies can be applied widely in both sides service and manufacturing sectors. There are wide available techniques to control product or process quality. Among them are statistical process control (SPC) tools, acceptance sampling, fail mode and effects analysis (FMEA), six sigma, design of experiments (DoE). Quality has become a decisive factor in attracting customers. Quality can be defined as fulfilling specification or customer’s requirement, without any defect. A product is said to be high in quality if it is functioning as expected and reliable. Quality control is an activity to ensure that items are fulfilling these criteria. Most of tools and techniques to control quality are statistical techniques. Quality control techniques can be classified into basic, intermediate and advance level, but there is no consensus among researchers in the classification. For example, Xie and Goh (1999) regard DoE as an intermediate level technique whereas Antony et al (1998) classified the techniques as advanced. Nevertheless, the content is more important than classification. Among, the basic techniques are Statistical Process Control (SPC). SPC is a statistical approach for assisting operators, supervisors and managers to manage quality and eliminate special cases of variability in a process (Oakland 2003). The initial role of SPC is to prevent product or process deterioration rather identifying product or process deterioration, but Xie and Goh (1999) suggest for its new role to actively identifying opportunity for improvement. Fail Mode and Effect Analysis (FMEA) is a powerful method to detect where exactly problems can occur and prioritize possible problems in order of their severity (Dale et al, 2003). The tool is useful to identify problems in product, i.e. design FMEA as well as to troubleshoot problems in process, i.e. process FMEA (Xie and Goh 1999). Six-sigma is also a statistical tool for ensuring defect free products through process continuous improvement (CI). The term Six-Sigma originated at Motorola and many organizations have set goal towards a six sigma level of performance (Breyfogle and Cupello 2001). The application of six-sigma has been mainly used in manufacturing industry. An example of the use of six-sigma in non manufacturing industry is in software development (Mahanti and Antony 2005) Process Capability study is an efficient method to examine the capability of a process to produce items that meet specifications. The method gains rapid growing interest due to increased use of quality system QS9000, where use of process capability studies is requested (Deleryd et al, 2009). The findings from capability study might need adjustment of process using other statistical techniques such as SPC or DoE. Capability studies conducted Motorcu and Gullu (2004) and Srikaeo et al (2005) show that the machine tool and process capability and production stability was evaluated and necessary steps to reduce poor quality production was carried out using other statistical techniques. Acceptance Sampling is another statistical technique to make a decision whether to accept or reject a lot based on the information from the sample. The application of acceptance sampling allows industries to minimize product destruction during inspection and testing and to increase inspection quality and effectiveness. The application of acceptance has been mainly used in manufacturing industry. Similarly, its application in non manufacturing industry is widely reported such as. Quality control is the activity we use to manage our businesses. It is based on integrating quality principles into everything we do, it has the power to direct and process our efforts and ensure that we meet the needs of our customers, employees and communities at large. Thus the philosophy underlying the implementation of quality control strategy is for the company or organization to see customers and clients as the vital key to their company’s success. It means that companies with quality control concepts see their (corporate performance and productivity) through the eyes of their customers and clients and then measure them against customer/client expectations. Such company will serve the customers best by providing quality goods and services. The predominant notion of such company is not how to make initial profit, but to give quality service to their customer. It should, however, be borne in mind that implementing quality control concept and techniques require substantial measurement and considerable survey and research. In other words, it implies that to improve quality, company or organization must regularly carry-out research or survey to evaluate products and services. The concept of quality as we think of it now first emerged out of industrial revolution. Decades, have witnessed rapid development of some concepts and principles along this line. The history of quality control is undoubtedly as old as industry. During the middle ages, quality was to large extent controlled by the long period of training and development required by the guilds. This training instilled pride in workers for quality of a product. When the concept of specialization was introduced during the industrial revolution, workers found that they no longer made their entire product only a portion and this change brought about decline in workmanship because most products manufactured during the period were not complicated. But as products became more complicated and jobs more specialized, it became necessary to inspect products after manufacturing. In 1924, Schewhart of Bell Telephone Laboratories developed a statistical chart for control of product variables and this was considered to be the beginning of statistical quality control (SQC). Later in the same decade, H.F Dodge and H.G Roming, both of Bell Telephone Laboratories, developed the area of acceptance sampling a substitute for 100% inspection. In 1946, the American Society for Quality was formed. This organization through its publications, conferences and training sessions prompted the use of quality for all types of productions and services. In 1950, Edwards Deming, who learned statistical control from Schwart, gave a series of lectures on statistical methods to Japanese engineers and on quality responsibility to Chief Executive Officers of the largest organizations in Japan. Also in 1954, Joseph Juran made his first trip to Japan and further emphasized management’s responsibility to achieve quality. Using these concepts Japanese set the quality standards for the rest of the world to follow. This resulted in the formation of the first quality control circle in Japan by 1960 for the purpose of quality improvement using simple statistical techniques. By late 1970s and early 1980s US managers were making frequent trips to Japan to learn about the Japanese miracle. Here in Nigeria, Standard Organization of Nigeria (SON) is one of the public agencies established by the government whose aim is for the welfare of the consumers. It is formed for the purpose of ensuring that products and services conform to certain specified standard. It stipulates quality, weights and measures that must be conformed by business. 1.2 Statement of the problem. This research work is carried with main aim of evaluating quality control measures on productivity in Benue Brewery Limited (bbl). An appropriate quality control measure is not just to identify or flags those factors that could directly affect the quality of goods and services but also to maintain an environment in which all employees are empowered to participate as a team in determining, assuring, measuring and improving the quality of the organization. It includes the use of facts and data gathered from the research survey to implement quality control philosophy with overall aim of increasing customers’ satisfaction and profitability. Thus, the basic philosophy of quality control will be examined in detailed and their interplay in having total quality. Upon examination of these problems, suggestions and recommendations will be made based on result of findings emerging from tested steps. 1.3 Objectives of study. Since, there are a lot of competitions in the brewery industries here in Nigeria and in order to stay in the struggle, they have no other option other than to adopt and implement quality control measures in all the activities of their industries which will also give rise to the amount of profits they make. The objective of the study includes: Evaluation of impact of quality control measures on production at bbl. Evaluation of process of production at bbl and make recommendation on how best to implement quality control in order to enhance productivity and also recommend which measures to be taken. 1.4. Significance of the study. The significance of this research work stems from impact and importance of quality control on productivity. Since most industries in Nigeria are being limited as a result of management techniques and skills from the large reservoir of potentials and existing materials that would aid success in the industry. This research is very significant as proper and adequate applications of sound measures will yield high corporate performance and productivity. This research will therefore reveal most important information about quality control, its techniques and concepts and also proffer some useful information to industries or individuals etc. that would like to implement it. It is also hoped that this research will stimulate industries to re-examine its management policies, techniques and measures by embracing quality control towards improving their corporate performance and productivity. 1.5. Scopes and limitations of the study. In this research, the scope is limited to evaluating the impact of quality control on the process of production in manufacturing industry. This research shall focus on the volume content of the products produce in Benue Brewery Limited (bbl) as a case study. It is a company that engaged in the production beer (more lager beer) CHAPTER TWO 2.0 LITERATURE REVIEW. 2.1 Review. The world economy has undergone rapid changes during the past two decades with the advent of global competition to an extent that almost every company (large or small) is touched by it in some ways. As creativity and innovation are necessary for bringing forth the change required to obtain competitive advantage, quality is the most effective factor a company or organization can use in the battle for customers/ clients. To be competitive, the customers must be satisfied and to satisfy the customers we must focus on quality. Quality control provides the philosophy and driving force for designing quality in order to delight the customers by focusing on best value of a company’s products and services. 2.2 Overview of quality control. Quality control is those activities and techniques used to achieve and maintain a high standard of quality in a transformation process. They may include systematic inspection of inputs and outputs, or a sample of input and output at various stages in their transformation to ensure that acceptable tolerances are not being exceeded. They may also involve a statistical analysis of data produced by the sampling (particularly in line production), benchmarking, continuous improvement (CI) and supplier partnering. In this case, in traditional organizations, management has to balance the costs incurred against the customers’ goodwill. Quality control is also concerned with finding and eliminating the causes of quality problems. Since quality control deals with quality of products and services, it seems important that the first step towards understanding the meaning of the phrase would require an understanding of the word quality. The word quality is often used to describe goods and services. Quality can be defined as a measure of the degree to which a particular product or service satisfies customers expectations with respect to tangible and intangible features of the product or service. However, Andrew .J. Marlow (2006) view quality as integral part of all products including services. It is an important consumer decision criterion in selecting among competitive products. Deming (1986) saw quality as aiming at the needs of the customers (present and future). Robert Kotler (1994) view a product’s quality as the ability to perform its functions. It includes the product’s overall durability, reliability, precision, ease of operation and repairs and other valued attributes. Although, some of these attributes can be measured objectively from marketing point of view, but quality should be measured in terms of buyers’ perception. Sullivan (1986) showed evidence on this issue when he defined seven stages of quality in Japan in order of increasing level of quality to include: product oriented, process oriented, system oriented, humanistic, society, cost oriented and quality function deployment (QFD). Juran defined quality as fitness for purpose. While Cro sby (1979) saw quality primarily as conformance to requirement. Broh (1982) defined quality as the degree of excellence at an acceptable price and control of variability at an acceptable cost. However, quality improvement has become the key factor for the success and growth of any business organization. Investment on quality improvement gives rich returns. Japan is the best example. There are many different ways in which quality can be approached, so one might wonder which one is the best for technical documentation. Unfortunately, there is no simple answer because quality is relative. It depends not only on the subject matter, but also on perceptions of quality from different view point. A company’s executive board might approach quality in terms of valve for money. They want technical documentation that can be produced quickly and cheaply. An engineer’s approach to quality might be one expressed in terms of technical accuracy and completeness. All approaches to quality can be combined to create a system from whichever angle you choose to implement a quality control system. You should start with the following plan: Have a clear definition of what is to be achieved and when (typically identified in the content of specification and project plan) Be clear about the activities and functions that are needed to be performed (which can be documented as codes of practice) Implement a control system in which activities, functions and outcomes can be monitored and, if necessary revised Unfortunately, like as said earlier, most of these definitions are subjective. Although the manufacturing-base and product-base approaches are objective, quality has to be defined by the company or organization concerned. Having agreed that quality is a necessary prerequisite for any company operating in today’s highly competitive business environment, it is therefore, implied that as quality varies from one company to another, it also dependent on their mission, policy and other elements that guide the company in the realization of its corporate goals. It is therefore, a common knowledge that in the manufacturing sector, quality is everything essentially, it is the product. From an institutional point of view, quality control can cover not just products, services and processes, but also people. It also maintains environment in which all employees are empowered to participate as a team in determining, measuring and improving quality of a company. It involves the examination of a product, service or process for certain minimum levels of quality. The main aim is to identify products or services that do not meet a company’s specified standard of quality and also to use facts and data to implement measure with the overall aim of increasing customers’ satisfaction, profitability and job satisfaction. According, to ISO 9000(International Organization for Standard), quality control is the operational techniques and activities that are used to fulfill requirements for quality. Adsit, D. (2007) defined quality control as the most necessary inspection control of all in cases where, despite statistical control techniques or quality improvements implemented, sales decrease. He further opined that if the original specification does not reflect the correct quality requirements quality control be inspected or manufactured into the product. Deming (1950), fourteen points that inspecting product for quality after they were manufactured was unacceptable. Instead, he proposed a process known as statistical quality control (SQC) that would use closely monitored performance measures to gauge quality as a product was being manufactured. Quality control may include whatever actions a business deems necessary to provide for control and verification of certain characteristics of a product or service. The basic goal of quality control is to ensure that the products, services or processes provided meet specific requirements and are dependable, satisfactory and fiscally sound. Essentially, quality control involves the examination of a product, service or process for certain minimum levels of quality. The goal of quality team is to identify products or services that not meet the company’s specified standards of quality. If a problem is identified, the job of a quality control team or professional may involve stopping production temporarily depending on the particular service or product, as well as the type of problem identified, production or implementation may not cease entirely. Usually, it is not just the job of a quality control team or professional to correct quality issues, typically, other individuals are involved in the process of discovering the cause of quality issues and fixing them. Once such problems are overcome, the product, service or process continues production or implementation as usual. As stated earlier, quality control can cover not just products, services or processes but also employees, because employees are an important part of any company/organization. If a company has employees that don’t have adequate skills, training, have trouble understanding directions or are misinformed, quality may severely diminished. When quality control is considered in terms of human beings, it concerns correctable issues. However, it should not be confused with human resources issues 2.3 The history of quality control. The Japanese were the first to adopt Deming’s fourteen points with great success. As an example, Deming learned of one Japanese factory that doubled production in just one year and was expecting to gain an additional twenty percent improvement the following year, with no increase in the amount of hours worked. All this occurred as a result of simply improving quality. What is most significant about this achievement is the year it happened 1951 many American and European companies chose to ignore these dramatic results and nearly perished as a result. Critics contend that the time American manufacturing plants realized that quality control was a significant issue, it was in late 1970s and Japanese firms such as Honda and Sony were taking over large portion of the American consumer market. In 1990s, most American firms have embraced quality control practices. Analysts indicate that when firms first began adopting these principles, many went too far, becoming bogged down in quality control charts and measurements of inconsequential operating factors. In too many cases, American industries went from ignoring statistical quality control (SQC) to applying it to every single facet of a business, no matter how small. This overemphasis quickly disappeared, however and has been replaced by a commitment to overall quality control that is unprecedented. Because Japan has been practicing quality management since 1950s, they are the leader in producing quality products in a number of industries and are still the role for American companies to emulate. For example, a study of â€Å"air conditioning industry in the early 1990s found that the worst Japanese air conditioning plant had an error rate that was less than one half of the best American company. And this drastic difference is largely due to the Japanese adherence to one of Deming’s most important idea that quality should be, â€Å"designed into† a product instead of â€Å"inspected out†. Japanese firms treat suppliers as equal, sharing information with them as if the suppliers were an internal department of the company. This ensured that quality is already a part of the product before it is even manufactured. 2.4 Quality assurance (QA). Quality assurance is all those planned and systematic activities implement to provide adequate confidence that an entity will fulfill requirements for quality. Often, quality control is confused with quality assurance. Though the two are very similar, there are some basic differences. Quality control is concerned with the product while quality assurance is process- oriented. Even with such a clear cut difference defined, identifying the difference between the two can be hard. Basically, quality control involves evaluating a product, activity, process or service. By contrast quality assurance is designed to make sure processes are sufficient to meet objectives. Simply put, quality assurance ensures a product or service is manufactured, created or produced in the right way while quality control evaluates whether or not the end result is satisfactory. The objective of quality assurance is not just to reject defective products, but to systematically investigate the causes of defects so that they can be eliminated. The figures below show the systematic diagrams of steps utilized by quality control and quality assurance in solving problems and how the two relates with each other. Fig.2.1 Typical quality control steps Fig.2.2 Typical quality assurance steps Difference between quality control and quality assurance Quality control Quality assurance Product Process Reactive Proactive Line function Staff function Find defects Prevent defects 2.5 Statistical quality control (SQC). Statistical quality control is use to describe the set of statistical tools used by quality professionals to tackle quality issues. Descriptive statistics. They are used to describe quality characteristics and relationship. Included are statistics such as: the mean, standard deviation, the range and a measure of the distribution data. Statistical process control (SPC). This involves inspecting a random sample of the output from a process and deciding whether the process is producing products with characteristics that fall within a predetermined range. SPC answers the question of whether the process is functioning properly or not. Acceptance sampling. This is the process of randomly inspecting a sample of goods and deciding whether to accept the entire lot based on the results. Acceptance sampling determines whether a batch of goods should be accepted or rejected. All three of these statistical quality control categories are helpful in measuring and evaluating the quality of products or services. 2.6 Components of quality control. These are the key components of quality control that were preached by Deming and practiced by the Japanese. a. Benchmarking It is a continuous process of measuring products, services and practices against your strongest competitors. It means using the best companies as the yardstick against which your company measures itself. If your company comes up short, then improvements must be made to ensure that your products are just as high in quality as those of your competitor. To successful benchmark, a company must first look closely at its own practices and conduct a rigorous self assessment once that self assessment is completed, the company has a good idea of where it stands on quality issues and can successfully compare itself to other companies. The self assessment must be honest and thorough. It should identify weaknesses, but should also highlight the strengths. Improving weaknesses that are identified should be tied to state company strategic aims. b Supplier Partnering. This is an increasingly common practice in the United States. Simply put, it means that manufacturers work directly with their parts and component suppliers to improve quality at the supplier’s location. This can involve direct participation in the supplier’s operations. That is, staff from the manufacturers might work on site at the supplier’s office or provide technical assistance and equipment or simply a very close working relationship rather than a simple business transaction between two unrelated companies. c Continuous Improvement (CI). This is a method for improving every facet of a company’s operations and increasing competitiveness by developing a company’s resources. The improvement can involve many goals producing products zero defects or achieving 100 percent customer satisfaction but CI has the same basic principles no matter what the goal Involve the entire company at all levels Find savings by improving existing processes, not by investing more money Gather data about company operations and quantify that data, which becomes the baseline against which improvements will be measured Do not forget that common sense is perhaps the most important component of CI Do not just give lip service to improvement-implement or practice ideas. d Quality Circle. It originates from Japan in 1962, and was introduced in United States in the early1970s. By the mid 1970s thousands of manufacturing plants, banks, hospitals and government agencies had implemented it. A circle consists of 3-12 employees from a given department and a representative of management. They meet on regular basis on company time to examine a limited range of issues related to department, identify and analyze problems and propose solutions. The focus of the circles is on improving of both the quality of the product and the product process. The members may consist of operators, supervisors, managers and so on. A good quality circle tries to overcome barriers that may exist within the prevailing organizational structure so as to foster an open exchange of ideas. The group members feels a sense of insolvent in the decision making process and develop a positive attitude towards creating a better product or service. 2.7 Implementation of Quality Control The expected stumbling blocks in implementing quality control come from the technical aspects of the tools (Grigg and Walls 1999). Therefore, the applications of quality control techniques require knowledge and training. Sufficient exposure to quality concepts and technical ability need to be considered to ensure that quality control activities are really efficient. This is particularly important if the industry intends to try new quality control or implement a quite complex and tedious quality control. The training does not only give important information and knowledge to workers but also build confidence and acceptance from them. ? CHAPTER THREE 3.0 METHODOLOGY 3.1 Method of Data Collection. In the course of this project work, due to time and financial problems, the population of the study is limited to Benue Breweries Limited (bbl), Makurdi Benue State, makers of more lager beer. Data collection method used is Random sampling method. Random sampling method which is the purest form of probability sampling, probability in the sense that each member of the population has a known non-zero probability of being selected. The reason for choosing this method is to allow each member of the population equal and known chance of being selected. Data were collected on daily basis for four consecutive days, with each day twenty-five bottles were selected. The main aim of using this procedure is to allow the products and production process to be well monitored in order to make good decision, because a situation whereby on ‘Day 1’ production process could be excellent while the following day may encounter some shortcomings which may be due to mal-functioning of the machines or faults, that is to say any decision taken based on the ‘Day1’ will continue to affect the quality of production process in this company until proper inspection is carried out. And also the choice of this procedure is to help reduce the cost incurred. After each day collection, each sample is measured and recorded for the four consecutive days after which they will be analyzed. 3.2 Method of Data Analysis. The data analysis was based on the data collected from bbl for the four consecutive days which were represented in a distribution table in chapter four of this work. The data collected were processed and interpreted using some Statistical Quality Control (SQC). They are: Descriptive Statistics. They are use to describe quality characteristics. They will be used to compute the data collected which will also be used to compute both the Upper Control Limited (UCL) and the Lower Control Limit (LCL) and also the Centre line used in both mean and range control charts. The descriptive statistics that will be used in chapter four in analyzing the data collected are mean and range. The Mean. It measures the central tendency of a set of data. It is defined as the sum of all observation divided by the total number of observations. It is given by: X = ?_(i=1)^n?X i 3.1a n X = the mean of the sample. Xi = observation i, i = 1, 2, 3†¦n. n= the number of observation. In the course of this research work, in chapter four, the mean of each sample number was first calculated after which the average of the mean of the samples was calculated which was used as the centre line of the mean control chart. The average of the sample means is given by, W/E=E/RT X = ?_(i=1)^nX/n ? 3.1b n X = the average of the sample means. X = the mean of the samples. n = the number of observation. The Range. It measures the difference between the largest and the smallest observation. In the course of this research work, in chapter four, the mean of the sample range was used to compute both the Upper Control Limited (UCL) and the Lower Control Limit (LCL) of both the mean and range control charts. While the mean of the total sample ranges gives the Centre Line (CL) used in range control chart. The range is given by. R = XL XS 3.2a R = the range of a sample XL = the largest observation of a sample. XS = the smallest observation of a sample. The mean of the sample ranges is given by R = ?_(i=1)^n?R 3.2b n R = the mean of the total sample range. R = the range of a sample. n = the total of the sample. a Acceptance Sampling. It is a method used to make a decision as to whether to accept or to reject lots based on inspection of samples. The objective is not to control or estimate the quality of lots, only to pass a judgment on lots. It is adopted in order to reduce the cost incurred due to product destruction during inspection and testing. b Control Chart. 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. It 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. The x axis represents samples (#1, #2, #3, and #4) taken from the process over time while the y axis represents the quality characteristic that is being monitored (milliliter of liquid). The center line (CL) of the control chart is the mean, or average, of the quality characteristic that is being measured. The upper control limit (UCL) is the maximum acceptable variation from the mean for a process that is in a state of control. Similarly, the lower control limit (LCL) is the minimum acceptable variation from the mean for a process that is in a state of control. In the course of this research work control charts for variables (mean and range charts) are used because they are use to monitor characteristics that can be measured and have a continuous scale (such as weight or volume), in which volume content of the bottles is the major concern of this research work. In the mean chart(X-bar chart), the sample means are plotted in order to control the mean of a variable (volume) and also to detect any shift in the mean of product, while in the range (R-chart), the sample ranges are plotted in order to control variability of a variable and also to detect any shift in the dispersion. The reason for using both of the charts together were both the mean and the variation (spread) has to be under control. For computing both the upper and lower limit of mean chart is given by the below equations: Lower Control Limit (LCL) = X – A2 R 3.3a Upper Control Limit (UCL) = X +A2 R 3.3b X = the average of the sample means. R = the mean of the sample ranges. A2 = factor for control limit and has value equal to 0.73 for sample size n = 4. The Center Line (CL) is given by the average of the sample means= X For computing both the upper and lower limit of range chart is given by the below equations: Lower Control Limit (LCL) = D3 R 3.3a Upper Control Limit (UCL) = D4 R 3.3b R = the mean of the sample ranges. D3 and D4 = factors for control limit and have values equal to 0 and 2.282 respectively. 3.3 Measurement of the volume content of the bottles. In order to understand the whole processes involved, some certain quality terminologies have to be defined in terms of this research work. They are: Product Specification. It is often called tolerance .it is a preset range of acceptable quality characteristics, such as product dimensions. For a product to be considered acceptable, its characteristics must fall within this preset range. In this work the product specification used in bbl ranging from 600ml to 630ml. Defect. It can be defined as a departure of a quality characteristic from its intended level that occurs with a severity sufficient to cause to cause an associated product or service not to satisfy the intended requirement. In this work anything below 600ml or above 630ml is considered as a defect, because that is the product specification used in bbl. Materials. These are the materials used in this research work. They are: 1000ml measuring cylinder, a bottle crown opener, octanol (an organic solution), empty crates and a basin. Procedure of Measuring the Volume Content of the Bottles. Firstly, samples were randomly selected from the population. 1000ml measuring cylinder was provided which I ensured that it was not wet inside. The opener was used to remove the corks of the selected bottles. Then two drops of octanol were put into the bottles and was allowed for few minutes to dissolve the foams, after which the content of the bottle was turned into the cylinder. Readings were taken and it was recorded. These steps were repeated for all the samples collected. 3.4 Problems and Limitation of Data Collection. One of the steps in empirical research is to determine the most important obstacles to the research. A research is a process of discovering the unknown through the known, and in achieving this, input such as time, energy and costs are used for the benefits or value in terms of contribution to knowledge. In spite of these efforts put in place, it is important to mention that some extraneous circumstance could have created some imperfection in the methodology adopted. Apart from personal sacrifices, energy and money, a lot of time is required in the search of information, data collection and conducting of random sampling. Another problem that limits the quality of the research work was the non-availability of Nigerian Textbooks that could fully describe the situation of quality control in Nigeria. Thus, this research had rely largely on foreign textbooks, journals and periodic. In the next chapter the values of the measured volume of the samples gathered were regarded as the data and were presented on a data distribution table for analysis and interpretation. CHAPTER FOUR 4.0 DATA PRESENTATION, CALCULATION AND DISCUSION. 4.1 Data Presentation and Calculation. Having concluded investigations to collect the necessary data, the focus of this chapter therefore is to present and analyze them in a form that will make the important features of the subject to be easily grasped and interpreted. This will enable the researcher evaluate the effect of quality control on productivity in bbl. It is expected that the results presented would be used as a guide in forming an opinion and recommendations on strategies and techniques for improving productivity. The results of the practical analysis were based on the data collected from one hundred bottles properly selected, measured and recorded collected from Benue Breweries Limited. This section involves presentation of data and calculation of the following: the samples mean, the sample ranges, the average of the sample mean and the mean of the sample ranges. Table 4.1 represents the raw data (unprocessed data) from the case study, while Table 4.2, represent the mean and range table which presents both the calculated means and ranges of the samples presented on the Table 4.1 Table. 4.1: Raw data distribution table Sample Number Observations (bottle volume in ml) 1 2 3 4 1 616 617 619 616 2 617 620 618 621 3 619 618 619 619 4 616 622 620 617 5 618 618 618 616 6 620 620 619 617 7 618 618 622 616 8 618 619 615 616 9 618 619 620 620 10 619 618 620 617 11 616 620 619 616 12 616 621 620 616 13 618 618 617 618 14 619 620 618 620 15 618 620 616 621 16 617 620 616 618 17 618 619 621 618 18 620 620 618 619 19 620 618 618 616 20 618 620 622 616 21 616 621 617 617 22 617 621 617 617 23 617 618 616 617 24 619 620 619 621 25 618 618 620 620 Calculation I. This involves the calculation of both the means of the samples and ranges of the samples using equations presented in the chapter three. Using the equation 3.1a the mean of the samples can be calculated X = ?_(i=1)^n?X i n Sample no.1: X1= 616+617+619+616 4 X1= 617.0ml. Sample no.2 X2 ¬ = 617+620+618+621 4 X2 = 619.0ml. Sample no.3 X3 = 619+618+619+619 4 X3 = 618.5ml. Sample no.4 X4 = 616+622+620+617 4 X4 = 618.8ml. Sample no.5 X5 = 618+618+618+616 4 X5 = 617.5ml. Sample no.6 X6 = 620+620+619+617 4 X6 = 619.0ml. Sample no.7 X7 = 618+618+622+616 4 X7 = 618.5ml. Sample no.8 X8 = 618+619+615+616 4 X8 = 617.0ml. Sample no.9 X9 = 618+619+620+620 4 Sample no.10 X10 = 619+618+620+617 4 X10 = 618.5ml. Sample no.11 X11 = 616+620+619+616 4 X11 = 617.8ml. Sample no.12 X12 ¬ = 616+621+620+616 4 X12 = 618.3ml. Sample no.13 X13 = 618+618+617+618 4 X13 = 617.8ml. Sample no.14 X14 = 619+620+618+620 4 X14 = 619.3ml. Sample no.15 X15 = 618+620+616+621 4 X15 = 618.8ml. Sample no.16 X16 = 617+620+616+618 4 X16 = 617.8ml. Sample no.17 X17 = 618+619+621+618 4 X17 = 619.0ml. Sample no.18 X18 = 620+620+618+619 4 X18 = 619.3ml. Sample no.19 X19 = 620+618+618+616 4 X19 = 618.0ml. Sample no.20 X20 = 618+620+622+616 4 X20 = 619.0ml. Sample no.21 X21 = 616+621+617+617 4 X21 = 617.8ml. Sample no.22 X22 = 617+621+617+617 4 X22 = 618.0ml. Sample no.23 X23 = 617+618+616+617 4 X23 = 617.0ml. Sample no.24 X24 = 619+620+619+621 4 X24 = 619.8ml. Sample no.25 X25 = 618+618+620+620 4 X25 = 619.0ml For the Range of the samples. Using the equation 3.2a the range of each sample can be calculated. R = XL-XS Sample no.1 R1 = 619–616 R1 = 3 Sample no.2 R2 = 621–617 R2 = 4 Sample no.3 R3 = 619–618 R3 = 1 Sample no.4 R4 = 622–616 R4 = 6 Sample no.5 R5 = 618–616 R5 = 2 Sample no.6 R6 = 620–617 R6 = 3 Sample no.7 R7 = 622–616 R7 = 6 Sample no.8 R8 = 619–615 R8 = 4 Sample no.9 R9 = 620–618 R9 = 2 Sample no.10 R10 = 620–617 R10 = 3 Sample no.11 R11 = 620–616 R11 = 4 Sample no.12 R12 = 621–616 R12 = 5 Sample no.13 R13 = 618–617 R13 = 1 Sample no.14 R14 = 620–618 R14 = 2 Sample no.15 R15 = 621–616 R15 = 5 Sample no.16 R16 = 620–616 R16 = 4 Sample no.17 R17 = 621–618 R17 = 3 Sample no.18 R18 = 620–618 R18 = 2 Sample no.19 R19 = 620–616 R19 = 4 Sample no.20 R20 = 622–616 R20 = 6 Sample no.21 R21 = 621–616 R21 = 5 Sample no.22 R22 = 621–617 R22 = 4 Sample no.23 R23 = 618–616 R23 = 2 Sample no.24 R24 = 621–619 R24 = 2 Sample no.25 R25 = 620–618 R25 = 2 Table. 4.2: Mean-Range distribution table. Sample Number Observations (bottle volume in ml) Mean(ml) Range 1 2 3 4 X R 1 616 617 619 616 617.0 3 2 617 620 618 621 619.0 4 3 619 618 619 619 618.5 1 4 616 622 620 617 618.8 6 5 618 618 618 616 617.5 2 6 620 620 619 617 619.0 3 7 618 618 622 616 618.5 6 8 618 619 615 616 617.0 4 9 618 619 620 620 619.3 2 10 619 618 620 617 618.5 3 11 616 620 619 616 617.8 4 12 616 621 620 616 618.3 5 13 618 618 617 618 617.8 1 14 619 620 618 620 619.3 2 15 618 620 616 621 618.8 5 16 617 620 616 618 617.8 4 17 618 619 621 618 619.0 3 18 620 620 618 619 619.3 2 19 620 618 618 616 618.0 4 20 618 620 622 616 619.0 6 21 616 621 617 617 617.8 5 22 617 621 617 617 618.0 4 23 617 618 616 617 617.0 2 24 619 620 619 621 619.8 2 25 618 618 620 620 619.0 2 Total 15459.8 85 Calculation II. This involves the calculation of the average of the samples means and the mean of the sample ranges using equations presented in chapter three. Using the equation 3.1b the average of the sample means can be calculated. X = ?_(i=1)^n?X n X = 15459.8 25 X = 618.4ml Using the equation 3.2b the mean of the sample ranges can be calculated. R = ?_(i=1)^n?R n R = 85 25 R = 3.4 Calculation for the Lower and Upper control Limit for the Mean (X- bar) chart. The lower and the upper control limit for the mean chart can be calculated using equations 3.3a and 3.3b respectively. Lower Control Limit (LCL) = X –A2 R Upper Control Limit (UCL) = X + A2 R X = 618.4ml R = 3.4 A2 = 0.73 LCL = 618.4 – 0.73(3.4) LCL = 615.9ml UCL = 618.4 + 0.73(3.4) UCL = 620.9ml The centre line for the mean chart (CL) is give by the average of the sample mean = 618.4ml Fig. 4.1the Mean Control Chart Calculation for the Lower and Upper control Limit for the Range chart (R- chart). The lower and the upper control limit for the range chart can be calculated using equations 3.4a and 3.4b respectively. Lower Control Limit (LCL) = D3 R Upper Control Limit (UCL) = D4 R R = 3.4 D3 = 0 D4 =2.282 LCL = 0 x 3.4 LCL = 0 UCL = 2.282 x 3.4 UCL = 7.8 The centre line for the mean chart (CL) is give by the mean of the sample ranges = 3.4 Fig.4.2 the Range Chart 4.2 Discussion. In evaluation of the quality control on the product produced in bbl Makurdi, Benue State. The means and ranges of the data collected were calculated and used to plot the mean chart (fig.4.1) and the range chart (fig.4.2). The mean chart (fig.4.1) is used to measure the central tendency of the product while the range chart measured the dispersion of variance of the product. Since, it is possible to have a shift in the mean of the product but not a change in the dispersion. This shift could be detected by the mean chart. On the other hand, it is possible to have a shift in the dispersion of the product without a change in the mean and this could be detected by a range chart. Since, a shift can be either in mean or range, in order to monitor the process effectively both the mean and the range charts can be used. That is main reason that prompted the use of both charts in this work. From the plotted points on the mean chart (fig.4.1), it could be seen clearly that none of the plotted points is above the UCL or below the LCL rather cluster round the centre line (CL), this shows that the process of production in this company is under control. Also from the plotted points on the range chart (fig.4.2), it could also be seen clearly that none of the plotted points is above the UCL or below LCL, rather cluster round the centre line. This shows that the process of production in this company is under control. Generally, the essence of the upper and lower control limit is to help detect when a process is out of control (i.e. when any plotted value is above the upper limit or below lower limit). CHAPTER FIVE 5.0 CONCLUSION AND RECOMMENDATION 5.1 Conclusion. In evaluating and analyzing of data gathered in the course of this research work regarding quality control on productivity in the brewery sectors in Nigeria, the following can be drawn: There are sign that quality control concepts improve the performance of an organization in terms of cost reduction, increase in productivity, competitiveness and customer satisfaction. The concept of quality control has been highly welcomed in this company as a way of life for customer satisfaction making the customer delighted as well as staff and in achieving corporate goals and objectives Finally, the importance of quality control in achieving success in business can hardly be denied. Peters and Waterman (1982) found quality to be an important element in the pursuit of excellence. Quality is therefore the best assurance of customer allegiance, strongest defense against competition and the only path to sustained company growth and earnings. Involvement of all the members of the company in the system is crucial if improvement in the performance and productivity is ever to be achieved with the adoption of quality control. Though, this is not easy to achieve but it must come from personal example and commitment. In addition, there must be consistency in the system as this can help change the entire process and maintain the competitive edge which the company seeks to attain. From the findings of this research work, it can be concluded that the machines and processes use in production in this company are effectively functioning well. 5.2 Recommendations. In view of the findings, the following recommendations are made. The practice of quality control should be regarded as an ongoing activity. As long as there are new ideas, innovations, developments, there should be no end to quality control process, so as to be able to cope with the dynamism of the modern world. There is need for top management to be more committed to quality control, as well as providing an enabling environment to incorporate all within the system in the quality control process. Similarly, there should be quality control awareness campaign a well as quality control meetings where programmes/ideas can always be discussed. The company should intensify efforts on cost reduction exercise. This can be done by providing regular staff training programmes for the staffs as this will help increase their knowledge, skills and prepare them for future challenges. Regular routine maintenance should be conducted on the machines to ensure steady efficiency of the machines. Inspections should always be conducted, data collected and analyzed in order to detect when the production is going out of control. Determine where current and potential quality problems lie. Take corrective actions, using established formal systems to remove the root causes of the problem. Encourage individuals and groups to set quality improvement goals. Encourage employees to communicate to management any obstacles they face in attaining their quality improvement goal. Train all employees in quality improvement. REFERENCE Antony, J., M. Kaye, and A. Frangou (1998): A Strategic Methodology to The Use Of Advanced Statistical Quality Improvement Techniques.The TQM Magazine, 10(3), pp.169-176. Breyfogle, F.W and J.M Cupello(2001): Managing Six Sigma: A Practical Guide to Understanding, Assesing and Implementing the Strategy that Yield Bottom-Line Success. JohnWiley and Sons, New York. Dale, B.G., H.S. Bunney, and P. Shaw (2003): Quality Management Tools and Techniques: An Overview. In Dale, B. G. (ed): Managing Quality,(4th Edition), Blackwell, Oxford. Deleryd, M., R. Garvare, and B. Klefsjo (1999): Experiences of Implementing Statistical Methods in Small Enterprises. The TQM Magazine, 11(5), pp.341-350. Grigg, N. P. and L. Walls (1999): The Use Of Statistical Process Control in Food Packing: Preliminary Findings And Future Research Agenda. British Food Journal, 101(10), pp. 763-784. Mahanti, R. and J. Antony (2005): Confluence of six sigma, simulation and software development. Managerial Auditing Journal, 20(8), pp. 739-762. Motorcu, A. R. and A.K. Gullu (2004): Statistical Process Control in Machining, A Case Study for Machine Tool Capability And Process Capability. Materials and Design, 27, pp. 364-372. Oakland, J.S. (2003): Statistical Process Control, 5th ed., Oxford: Butterworth-Heinemann. Peters, T. and R. Waterman, (1994): In Search of Excellence in TQM, Macdonald Evans Inc. New York. Srikaeo, K., J. E., Furst, and J. ssAshton (2005): Characterization of Wheat Based Biscuit Cooking Process by Statistical Process Control Techniques. Food Control, 16, pp. 309-317. Xie, M. and T.N. Goh, (1999): Statistical Techniques for Quality. 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