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It has been said that the most universal quality is diversity. No two actions performed by an individual are exactly the same. Even in the physical sciences, which we think of being so accurate, repeated measurement by the same person or by different persons may vary and the means is accepted. Therefore, variability is inherent in nature and in all manufactured product.

Recognizing that variability is bound to occur, manufactures or buyer of manufactured goods often set standard to which their products must conform, with these they are to be considered satisfactory.

These standards with generally specify not only a desirable norms, but limit above and below this norms, within which a satisfactory item must lie.

It is believed that no two things are perfectly identical and this is due to assignable cause of variation, which can be due to poor input of materials of machine breakdown.

It may surprise some person to learn that two apparently parts made under carefully condition apart by the same machine, can nevertheless be different in many respect. Indeed, any manufacture process, have ever good is characterized by a certain amount of variability when the variability present in a production process is contained to chance variation, the process is said to be in a state of statistical control, such a state is usually attained by finding and eliminating trouble of the sort coursing another kind of variation called assignable variation, which may be due to poorly trained operators, poor quality raw materials, faulty machines settings, worn-out ports and the like since manufacturing processes are rarely free from trouble of this kind, it is important to have some systematic method of denting serious deviation from a state of statistical control when or it possible before they actually occur.

It is to this end that control charts are principally used. Gupta (1975) after examining method of quality control through inspection went into suitable system of inspection. This he said include that which detects as it occurs. He called for introduction of sample inspection to replace hundred percent in sections. He also said that this system is possible through statistical quality control techniques.



The purpose of this research is to

  1. Establish standard of quality for manufactured cement blocks that is produced in Ukeme Inyang and son industry
  2. Control the manufacturing process so that the standard of quality maintained in the production.
  3. Make recommendations that individual lots sold or purchase are acceptable quality in Ukeme Inyang and Sons and marked.

1.3     THEORETICAL ANALYSIS            

Statistical quality control is a technique that employs statistical methods as an aid in controlling quality. The main function of statistical quality control is to signal when there is a quality change. To buttress his point, he identified two methods of statistical quality control as;

  1. Process control
  2. Product control

Gupta (1973) explained process control to appraise the performance of each individual process to foresee the variability in the quality of output of each process in the immediate future or as the process is in progress. In produces production this is being completed then inspection is carried out to see it items produced are of required standard and if the are not, the whole lot is rejected.

Mille and Freund (1987) stated that, while examining the finished produced, those that do not meet these specifications limits should be rejected and production continued until good lots sized have been produced.

While quality control emphasized on the quality of future outputs, inspector the equality examined method of controlling quality of product to include provision of correct instruction prior to the product of an items to the operating personnel, however, the most important method are based on satisfactory technique ways of taking unsatisfactory production process was also suggested and they include machine adjustment, detects elimination in the raw material and replacement of unfit operation.

Ray (1980) said in achieving the descried quality, inspections therefore is a crucial factor in quality control and it involves the application of test and measuring devices to prepared products and performance with specified standard. By inspection, Ray (1980) said one may determine whether a given items falls within specified limits of variability and acceptable detect certain benefit derived from control and inspection may be summarized as follow:

  1. Adequate maintenance of quality necessary to satisfy customers and to meet the competition of rival production.
  2. Uniform quality of work necessary for the interchangeable ports method of manufacture.
  3. Prevention of waste of labor and machine time on work already known to be detected.
  4. Economic production is achieved through the reductive of detective work and consequently increases in the utilization of facilities and labour. This object of statistical quality control includes collecting of data in sound, unbiased manner and analyzing of result as to obtain satisfactory dependable and economic quality.

Statistical quality control is obtain maximum benefit out of production and inspection of data at lowest cost through variation in control, may be minimal but it does exist so, producers should set up standard of quality, for which product must conform, if the are to be considered satisfactory for use.

Moveover, product that falls outside the ranges of these specifications should be rejected and consider unfit for use. It is standard practice of customers to test samples of product for quality levels. It is possible for a customer to reject a consignment standard called producers risks. To accept a consignment which is below specification called the consumer is risks. The nominal quality level agreed by producer’s customers is called acceptable quality (AQL). A lower standard called the lot tolerance percentage detective (LTPD) is nominated by the consumers as the minimum acceptable standard.


1.3.1  Types of Control Charts 

A control chart is of two types:

The control chart measurement and that of attributes depending on whether. The observation with which we are concerned are measured or count data (data number of detective in a sample) control charts therefore consist of a central line corresponding to the average quality at which the process is to perform. The upper and lower control limits. These limits are choosing so that values falling beyond them are interpreted as indicating a back of control. By plotting result abstained from sample taken.

Periodically frequent intervals, it is possible to cheek by means at such a chart whether trouble has entered the process, when a sample point falls beyond control unit, one looks for trouble but even if the point calls between the control limit, a trained or some other systematic pattern may serve notice that action should be taken to avoid serious trouble. The control limit are also designated the warning and the action lines respectively.

The following charts are used in quality control anywhere. X – Chart, range – chart fraction, detective chart (P – chart) number of detective – chart (c – chart).


Sample Numbers

These line are use as follows, it point fall outside broken line that a signal that something is about happening but when it fall out the action lives, then producing should be stepped immediately in order to correct or adjust machine setting when the points falls close to the central lines a systematic pattern of trend slow that production is out of control.


1.3.2  Control Chart for Measurement   

  1. Means ( x ) – chart: The central line of an x – chart is given by M and the upper and lower and three sigma central limited are give by M and the upper and lower, and three sigma control limited are given by M ± Ab, where 3/n,  is standard deviation, n is the sized of each sample.
  2. Range Chart: The central lines and control limit of an R – chart are based on the distribution of the range of sample of sized train a normal population central line = c/2 and sigma control limit for the range are given by c/2 ± 3 c/3 .

1.3.3  Control Chart for Attributed

  1. Fraction –Defective and number of Defective Charts: These charts fall under control chart gained from measurement made on a finished product. Controls limited for a fraction detective chart are based on the sampling theory for proportions.

Thus, it is a standard is given, that is the fraction detective should take on some pre-assigned values p, the central line is p and three sigma control limited is given by p ±

  1. Defective – Chart: There are situation where it is necessary to control the number of detects in a unit of product, rather than the fractions detective or the number of defectives, central line = Z and three sigma control limited = 1 c ± 3 .

This research work will make use of means chart, range – chart and proportion defective chart. Now with compute all them in the different table of data analysis.



The Ukeme Inyang and sons blocks industry is confronted with a number of problems, for the purpose of this research, only production problem related to the quality of their product will be examined. For example, the thickness of skup block might be to think or too tin this can be as a result of inconsistent input of new materials or faulty setting of machine. Another example is on quality of building cement block produced, if cement block are very light and not durable, buyers will reject. Therefore, the aim of this research is to study variation on the products from measurement of width of cement blocks.


1.5     HYPOTHESIS      

The hypotheses under test are:

Ho: Deviation from standard does not depend on sized.

HI: Deviation from standard depends on size.



Since this research is aimed at studying result of various steps in productions process, at the end, the result will help in setting standard quality control in the company to determine whether quality of manufacture goods is satisfactory, to have sound basis for making specifications and to improve on existing techniques it needs the quality of manufacture goods is satisfactory.


1.7     LIMITATIONS   

It is very bad that this research is influenced and subjected to unavoidable and uncontrolled conditions. Thus, some of the limited are:

  1. The data used in this research work are collected through primary sources and as such it is known how accurate the data are and their recording procedures.
  2. There may be error in the data since there measured to eliminate and check them.


1.8     DELIMITATION    

This research topic is delimited to the statistical quality control measures in the production of building cement block and the data collected from Ukeme Inyang and sons block industry.

Through the company also produces different type of cement block and sizes. They produced four types of cement block in the Ukeme Inyang and sons block industry.



This research is based on the following assumptions:

  1. Data collected from the company is accurate.
  2. All measurement are assumed to be correct.
  3. Operators are assumed to the competent.



  1. Process Control: In process control, observation are made while production is still going on where there is a significant deviation from what is expected, the production process is matted and them necessary corrections are made before production process continues.
  2. Product Control: In production control, production is completed and than observations are made to see it productions is in line with what is expected.
  3. Lot Acceptance Sampling: A relative small sample from a lot of specified sized if the number is smaller or larger than the number known as the acceptance or rejection number then the cost is acceptance the acceptance and rejections number are established on probability basis.
  4. Quality: These characteristics or properties in a product that makes it marketable.
  5. Control: To keep within boundaries or to keep within a desired range.
  6. Quality Control: This is the keeping of these properties of a product under cheek for the liking of customers i.e. preserve the quality that attracts customers. Quality control also is regarded as a factor that determines the growth of any production company.





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