International Journal of Pure and Applied Sciences and Technology

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1 Int. J. Pure Appl. Sci. Techl., 15(1) (2013), pp International Journal of Pure and Applied Sciences and Techlogy ISSN Available online at Research Paper Statistical Quality Control of Manufactured Products (Case Study of Packaging at Lifespan Pharmaceutical Limited) C.N. Nnamani 1, * and S.H. Fobasso 1 1 Department of Mathematics, Ahmadu Bello University, Zaria- Nigeria * Corresponding author, (ncngene@abu.edu.ng) (Received: ; Accepted: ) Abstract: In the manufacturing environment, quality improves reliability, increases productivity and customer satisfaction. Quality in manufacturing requires the practice of quality control. This research work investigates the level of quality control in Lifespan pharmaceutical limited, makers of Lifespan Table Water. The study involves inspection of some randomly selected finished products on daily bases. The data on the number of sachets were collected two times (morning and afteron shifts) per day. This was done for three weeks. The physical observations (number of s) from the company were analyzed using statistical tools such as Descriptive Statistics (proportion and mean counts of s) and Control Chart for Attributes (P-chart and NP-chart). The proportion of sachets per day was found to be with upper and lower control limits of and respectively. Furthermore, this work shows that there are many points that fall out of the control limits. This means that the production process is out of control and needs a thorough and complete process inspection and verification. Even though the proportion of (which is about 3 s out of 100 every sachets) is t too high, the fact that the production process is t within control limits calls for a decisive action by the company. Keywords: Water, Defective, Production, Chart. Introduction The world ecomy 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 invation 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 customer/clients. To be competitive, the customers must be satisfied and to satisfy the

2 Int. J. Pure Appl. Sci. Techl., 15(1) (2013), 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. The basic goal of quality control is to ensure that the products, services or processes provided meet specific requirements and are dependable, satisfactory, affordable and physically sound (Hotelling, 1947). Quality control is made up of those activities and techniques used to achieve and maintain a high standard of quality in a transformation process at reduced cost. They may include systematic inspection of inputs and outputs at various stages in their transformation to ensure that acceptable tolerances are t 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 cost incurred against the customers goodwill. Quality control is also concerned with finding and eliminating the causes of quality problems. However, Andrew J. Marlow (2006) views 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 customers (present and futures). 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 buyer s 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 Crosby (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. Since 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 ather, 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 kwledge that in the manufacturing sector, quality is everything. 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 that do t meet the company s specified standards of quality (Woodall, et al., 2004). 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 t cease entirely. Usually, it is t just the job of the 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. Due to the general breakdown of infrastructure in Nigeria occasioned by poor or lack of maintenance and mismanagement of the nation s resources, many Nigerian localities, urban areas inclusive, have resorted to self help in the provision of basic amenities which, hitherto, have been seen (just as in other parts of the world) as fundamental human rights and basic responsibility of Governments. Despite the abundant natural water resources in our land, the promises of the Government in the area of provision of portable water have been elusive, even in the face of the Millennium Development Goals (Idris, 2012). This has led to a booming business of production of sachet water, popularly referred to as pure water in many oks and crannies of our communities. In many occasion, the pure water sachets are found to be of varying sizes and qualities due to lack of application of

3 Int. J. Pure Appl. Sci. Techl., 15(1) (2013), Statistical Quality Control (SQC) in the production process. This study applies SQC in the production process of Lifespan Pharmaceutical Limited as a baseline for such processes in Nigeria. Materials and Methods Method of Data Collection Data collection method used is random sampling method. Random sampling method is the purest form of sampling, probability in the sense that each member of the population has a kwn n- zero probability of being selected. The reason for choosing this method is to allow each member of the population equal chance of being selected. This study used primary data. The data were obtained using face to face interview with the operation manager of Lifespan Pharmaceutical Limited and personal observation during production for a space of three weeks. Lifespan Pharmaceutical Limited is among the major producers of sachet water in Zaria-Nigeria. The product of Lifespan Pharmaceutical Limited is highly consumed in Zaria and its environs. Within Kaduna State, it ranks among the most high patronised packaged water. The product of Lifespan Pharmaceutical Limited spreads as far as (and even beyond) Funtua in Katsina State Nigeria, Fulatan in Ka State Nigeria and anguwa Kahu in Plateau State Nigeria. The data were collected on daily basis for three consecutive weeks, some in the morning and some in the afteron. Each day twenty s were with 2000 sachets of water per. 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 day1 production process could be excellent while the following day may encounter some short coming which may be due to malfunctioning of the machine or faults, that is to say any decision taken based on the day1 will continue to affect the quality of the production process in this company until proper inspection is carried out. After each day collection, each is and recorded for the fifteen consecutive days after which they will be analyzed. Method of Data Analysis The tools used for this study are the p chart and the np chart for control of quality. These tools are appropriate for the control of quality when the variables are attributes in nature. It is purely binary in nature. Good or Bad and Yes or No are familiar terms commonly used to describe such processes. Attribute data must be converted to a form of variable data called discrete data in order to be counted or useful (Chanda, 2001). Attributes data are qualitative data that can be counted for recording and analysis. Examples include the presence or absence of a required label. The control charts based on attribute data are proportion (p) chart, number of units (np) chart, count chart (c), count-per-unit chart (u), quality score chart and demerit chart (D). The p chart and the np chart are the techniques used in this study. The p-chart is designed to control the percentage or proportion of s per while the np-chart is designed to control the number of s rather than the proportion of (Montgomery, 2008). The steps for constructing these charts are enumerated below. The steps in constructing the p-chart: 1. Compute the average fraction (P ) by dividing the number of s by the total number of units. This is the center line (CL); CL=P = x/n 1 2. Compute the upper control limit (UCL);

4 Int. J. Pure Appl. Sci. Techl., 15(1) (2013), UCL = P + 3 ( ) 2 3. Compute the lower control limit (LCL); LCL = P - 3 ( ) 3 The steps in constructing the np-chart are: 1. Compute the average number which represents the center line (CL); CL = 4 2. Compute the upper control limit (UCL); UCL = + 3 (1 ) 5 3. Compute the lower control limit (LCL); LCL = - 3 (1 ) 6 The data analysis is based on the data collected from Lifespan Pharmaceutical Limited for the three consecutive weeks which are represented in a distribution table. The data collected is processed and interpreted using some statistical quality control tools. These are Descriptive statistics, acceptance sampling and control chart. Table 1: Data collected in three consecutive Mondays

5 Int. J. Pure Appl. Sci. Techl., 15(1) (2013), Table 2: Data collected in three consecutive Tuesdays Table 3: Data collected on three consecutive Wednesdays

6 Int. J. Pure Appl. Sci. Techl., 15(1) (2013), Table 4: Data collected on three consecutive Thursdays Table 5: Data collected on three consecutive Fridays

7 Int. J. Pure Appl. Sci. Techl., 15(1) (2013), Result and Discussion The Control Limits for P and NP chart are given in the following table, Limits P NP LCL CL UCL (a) (b) Fig. 1: (a) p and (b) np chart for Monday productions One point more than 3 sigma from center line. Test failed at point 33 for both P-chart and NP-chart. Monday productions of Lifespan table water are out of control at only one point.

8 Int. J. Pure Appl. Sci. Techl., 15(1) (2013), (a) (b) Fig. 2: (a) p and (b) np chart for Tuesday productions The process for Tuesday productions does t present any unusual pattern so the process is in statistical control. The data were collected for three consecutive Tuesdays both in morning shift and afteron shift which make this process a benchmark when planning for process improvement. (a) (b) Fig. 3: (a) p and (b) np chart for Wednesday productions

9 Int. J. Pure Appl. Sci. Techl., 15(1) (2013), One point more than 3 sigma from center line. Test failed at point 37. Wednesday productions of Lifespan table water are out of control at only one point. (a) (b) Fig. 4: (a) p and (b) np chart for Thursday productions One point more than 3 sigmas from center line. Test failed at points: 21, 25, 33, 34, 35, 37, 38, 40, 41. Thursday productions of Lifespan table water are out of control at nine points.

10 Int. J. Pure Appl. Sci. Techl., 15(1) (2013), (a) (b) Fig. 5: (a) p and (b) np chart for Friday productions One point plotted more than 3 sigma from center line. Test failed at points: 22, 37 and 42. Friday productions of Lifespan table water are out of control at three points. Conclusion It can thus be concluded that the entire process at Lifespan pharmaceutical limited is out of control which implies that there are a lot of waste in input either financial or time consuming. For optimization of process output, there is a need for complete and vigorous process verification and checking so as to identify the causes of process been out of control. References [1] J.M. Andrew, Quality Control for Technical Documentation, Moonprint, [2] A. Broh, Managing Quality for Higher Profits, New York: Mc Graw-Hill, [3] M.J. Chanda, Statistical Quality Control, CRC Press, LLC, 2000 N.W. Corporate Blvd., Boca Raton, Florida 33431, 2001.

11 Int. J. Pure Appl. Sci. Techl., 15(1) (2013), [4] P. Crosby, Quality is Free, New York: Mc Graw-Hill, [5] W.E. Deming, Out of the Crisis, MIT Press, Cambridge MA, USA, [6] H. Hotelling, Multivariate Quality Control: Techniques of Statistical Analysis, McGraw-Hill, [7] D.C. Montgomery, Introduction to Statistical Quality Control (4th ed.), Wiley, New York, NY, [8] R. Kotler, Phel skin peeling, symposium on chemical skin peeling, Annual American Academy of Facial Plastic Reconstructive Surgery, San Diego, [9] W.H. Woodall, D.J. Spitzner, D.C. Montgomery and S. Gupta, Using control charts to monitor process and product quality profiles, Journal of Quality Techlogy, 36(2004), [10] A. Idris, The massive MDG fraud: How the health ministry steals from the sick and dying, Premium Times, July 20 (2012).