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In this research work titled “statistical quality control of premier soap in manufacturing industry” A case study of Pz cusson Plc Aba. The aim of this research work is to ascertain whether the product conform to the set standard of the industry and also to know if the color of the product is stable or out of control and finally to check if the is any significant difference in the mean weight of soap produced by Pz cusson. The data collected from the department of quality control of Pz cusson was analyzed using the mean X-chart, Range R chart P-chart and finally analysis of variance (ANOVA) to achieve the aims of this research work. Generally, through the use of mean X-control chart and Range R chart, with graphical representation of these charts, it was discovered that the product “premier soap conforms to the set standard of the industry. Also the analysis of variance indicates that there is no significant difference in the means weight of premier soap, since the product conforms to the set standard.
The reputation attached to an organization for the quality of its product is accepted as a key to its success and the future of its employees. To prepare in today’s economic climate, any organization and its suppliers must be dedicated to never-ending and more efficient ways to obtain products or services that consistently meet customer’s needs.
Prior to the 1900s, U.S industry was largely characterized by small shops making relatively simple product, such as candles or furniture. In these small shops the individual workers was generally a craftsman who was completely responsible for the quality of the work. The worker could get the quality through the personal selection of the materials, skillful manufacturing, and selected fitting and adjustment.
In the early 1900s factories sprang up, where people with limited training were formed into large assembly lines, products became much complex, the individual workers no longer had complete control over the quality of the product. A semi-professional staff, usually the inspection department, became responsible for the quality of the product.
1.0.1 SPECIFICATION, PRODUCTION AND INSPECTION
Before production starts, a decision is necessary as to what is to be made. Next, comes the actual manufacturing of the product. Finally it must be determined whether the product manufactured is what was intended. It is conferment to think of all matters related to quality of manufactured in terms of those three functions: specification production and inspection.
Statistical quality control should be reviewed as a list of tools, which may influence decision co-operation among those responsible for these three different function or decision at a higher level than one of them. For this reason, the techniques should be understood at a management level that encompasses all the three function. No production process is good enough to produce all items of production exactly alike, some variability is unavoidable.
The amount of this basic variability of the process is so great that, it is impossible to make all the product fall within the specific limits.
When control chart shows that this is true, and when the specification cannot be changed, the alternative are either to make a fundamental change in the production process that will reduce its basic variability or to the fact that it will always be necessary to sort the good product from the bad ones.
The quality responsibility was usually fulfillment by a 100% inspection of all the important characteristics. If there were any discrepancies noted, these problems were handled by the manufacturing department supervisor.
In essence, quality was attained by “inspecting the quality into the product”.
During the 1920s, Dr. Walter A Shewart of the Bell telephone laboratories, developed the concept of statistical quality control. He introduced the concept of controlling” the quality of a product as it was being manufactured, rather than inspecting the quality into the product after it was manufactured.
1.2 BRIEF HISTORY OF PZ CUSSON PLC
George Paterson and Goerge Zochorius set up a trading post in Sierra Lone in 1897. in 1899 Paterson Zochonis (Pz) opened a Brach office in Nigeria. They acquired their first soap factory in Nigeria in 1948.
In 1969, a manufacturing base was established in Ghana. Paterson and Zochonis entered the detergent and refrigerator markets simultaneously in Nigeria in the year 1973, Pz acquired cusson Group ltd, Pz started up soap manufacturing in Melbournic, Austrialia in 1976 Minerua S.A, a leading great edible oils and fats manufacturer was acquired in 1977.
Consequently, Pz production purchased its first soap factory in Kenya in 1983. Production started at this pethum Thani site in Thailand in 1986. in 1988, Pz cusson Indonesia was established, 1993, Pz brought the state-owned pollens Wrodaw in Poland, followed in 1995 by Pollena Uroda.
In 2002, Paterson Zochoris was changed to Pz cusson Plc. Pz cusson entered into a joint venture with Galnbia plc to supply evaporate milk and milk powder in Nigeria in 2003. In 2004, they acquired the Charles Worthinton haircare business.
Today, they deal not only on soap but also on Pharmaceuticals and confectories as well as treazers etc with its head office at No 45/47 Town planning way Illupeju industrial Estate Lagos.
1.3 BACKGROUND OF THE STUDY
Statistical quality control is generally described as the control of product quality by statistical methods. Various techniques developed by mathematical statisticians for the analysis of data may be used in control of product quality. This research work addresses the statistical quality control of soap manufacturing “premier soap” in Pz cusson ltd. However, it detailed the statistical techniques, application of control chart and analysis of variance.
Premier as the soap implies is soap which some notable people cannot do without. On the usage of soaps in Nigeria today, competition is very high.
1.3.1 STATISTICAL QUALITY CONTROL
This is the application of statistical techniques or procedures to industrial operations. It involves the technique of sampling at every stage of production and statistical inference about the variability of the product quality.
IMPORTANCE OF STATISTICAL QUALITY CONTROL
Some major economic of the statistical quality control includes the following.
i. It protects producers from having their products rejected when such products contain a relatively low number of defective i.e when such products conforms in quality and uniformity to specification.
ii. It protect consumers from accepting a product containing high number of defective.
iii. It provides full information about the quality of the goods being produced the implication of which guides the producer into knowing when to adjust the system.
iv. It encourages the producer to keep the process in control.
v. It protects the producer from imputing batch raw materials into process. Testing the raw material to know if they conform to specification before using them for production.
1.3.2 CONTROL CHART
Walter A.S of Bell telephone laboratories in a memorandum dated May 16, 1924 introduced the concept of the techniques is chronicled in a number of articles by Shewart and his 1931 Candmark book, economic control quality of manufacturing process.
The control chart usually consist of three horizontal lines. The top line represented the upper control limit, the bottom line which is the lower control limit, the center line, an acceptable average for the process based on specification or historical data.
The control chart is constructed in such a way that can plot the results of processing the quality of a manufactured product through periodic monitoring the manufactured process. Each line the process is monitored and at a point placed in the control chart. As long as the points falls within the two control limits, we do not question the quality of the product. But when a plotted points falls outside the control limit, this alert the production manager to possibility that the quality of the product is unacceptable.
PURPOSE OF CONTROL CHART
1. Control charts identifies hen assignable cause of variation or changes have entered the process.
2. It is also a graphical display of the actual measurement of a chart showing limit, which reflect the capability of the particular quality characteristics.
3. These charts indicate to workers, group leaders, quality control engineers, production supervisor and management whether the production of the part or service is “in control” or out of control”.
TYPES OF CONTROL CHART
Control chart for variables, control chart for attribute and control for the number of defect per unit.
Control chart for variables includes the Average control chart ( -chart) Range control chart (R) and δ chart (standard deviation).
Control chart for attributes: observations are recorded as either defective, or non-defective, and statistic of interest are the proportion defective in a sample of size n example P-chart.
1.4 STATEMENT OF THE PROBLEM
According to Osuala, (1987) the statement of a research problem services to elaborate upon the information in the title of the study.
Below are the important problems question for this study:
1. Does the product (-premier soap) conform to specification?
2. Does the colour of the conform the targeted standard?
3. Is there any significant difference between the mean weight of soap?
1.5 OBJECTIVE OF THE STUDY
The objective of this research work are:
1. To find out whether the production process is in statistical quality control.
2. To know if the colour of soap is out of control.
3. To find out if there is any significant difference in the mean weight of premier soap manufactured by Pz cusson plc or not.
1.6 STATEMENT OF HYPOTHESIS
Based on the problem above, the following
Hypothesis is deducted for the study:
1. Ho: The product does not conform to specification
H1: The product conform to specification
2. Ho: The colour of soap does not conform to standard
H1: The colour of soap conform to standard.
3. Ho: There is no significant different between the mean
H1: There is significant different between the mean
1.7 SCOPE OF THE STUDY
This research work covers the quality control process, problems and solution to the manufacturing industries, such as in the production of “premier soap in Pz cusson industry Plc Aba” on the quality control measure.
1.8 LIMITATION OF THE STUDY
This study was limited to the following factors:
i. Time factor
ii. For business confidentially, information on the various quantities of some components or raw materials were regarded as part of the organizations private affair. Example: quality of palm oil, distilled water etc.
1.9 DEFINITION OF TERMS
The following definitions are used within the context of this research work.
a. Quality of a product is a measure of the product ability to meet the expectations of the customer.
b. Statistical quality control: Is a technique or procedure of sampling at every stage of production and statistical inference about the variability of the product quality.
c. Control chart: is a graphical display of the actual measurement of a quality characteristics on a chart showing limit which reflect the process capability on the particular quality characteristics.
d. Control limit: These are limit showing the maximum range of variation permissible in the measured quality characteristics.
e. Process control: this is the act of observing the functions of each of the factors leading to the production of any goods on a continuous basis to ensure that the process or means of production is kept in control.
f. Product control: this is the act of observing different attributes of quality specification of a product with the aim of ensuring that the product conform to specification. This is done by taken a sample from a batch of inspection lot with the aim of accepting or rejecting.
g. Specification: Is a set standard to which a process is to conform to.
h. Standard: An average or normal required quality, quality, level, grade etc
i. Chance cause of variation: These are the inherent and uncontrollable variation malfunctioning associated with any process or experiment.
j. Assignable cause of variation: They are variation resulting from operational malfunctioning
k. Inspection by Attributes: A method of inspection where either the unit of product is classified as “defective” or “non defective”.
l. UCL: Upper control limit
m. LCL: Lower control limit
n. Tolerance limit: This provide a basis for acceptance or rejection of a finished product.