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Applications of Quality Control Techniques for Precision Engineering Industry

Quality Control Techniques Used in Precision Engineering Industry

You Are The Quality Control Manager In a Precision Engineering Company Which Produces Batch Quantities Of Small Components For Local Industry. a New Sales Director Has Joined The Company And He Has Asked You To Produce a Report On Applications Of Quality Control Techniques In Order To Get Him Up To Speed On How The Company Operates. For This Task You Will Describe How Typical Quality Control Techniques Are Used To Monitor The Accuracy Of Manufacturing Processes And Describe How Techniques Might Vary Dependant On The Type Of Process And The Limits Required.

Your Company Has Received a Request For 200 Hounsfield Test Pieces In Various Material Specifications, As a Test For a Potentially Much Larger Order. (The Drawing For The Test Pieces Is Appended.) The Company Has Recently Installed Three New Cnc Lathes. As Quality Control Manager You Must Decide What Measurements And Analysis You Must Carry Out To Calculate The Process Capability Index For These Machines. Explain What Is Required In An Email To The Production Manager.

There are no doubts quality is paramount in the production or manufacturing of products. Quality involves specific predetermined attributes of a commodity, which include color, weight, shape, composition, and dimensions, among others. Therefore, quality is performance of the product as per the demands made by the producer to the clients or consumers (Sinha, 2019).  Notably, the demands by producers can be explicit through the terms of the expectations of average consumer or written contract. On the other side, performance of a commodity involves the sole function or services that the commodity offers to the end user (Sinha, 2019). Generally, a commodity is defined as a quality product if it satisfies specific criteria for it functioning, during its time of manufacture and over a period of its use.

As a result, both quality assurance and control measures are used by manufacturers to ensure the products produced abide by the performance expectations. Quality control (QC) is a strategy in which the products are produced to conform to the specifications determined by the client’s demand and transforms into distribution and manufacturing requirements. Besides, the strategy aids in making manufacturing process “right” instead of discovering or rejecting deformed products (Sinha, 2019). Generally, QC is a technique in which products of uniform acceptable quality are manufactured. There are various advantages of QC; for instance, it aids the manufacturers in fixing responsibility of workers in the production process; besides, QC aid in reducing the costs of production by improving efficiency, standardization, and working conditions. Moreover, QC enables the manufacturer to evaluate whether the product conforms to the set standards, which further aids in the adoption of necessary actions to comply with the set standards.


There are two major methods used in quality control, which include inspection and statistical quality control (SQC). Inspection involves critical checking of products and the process used; however, it is only applicable on small scale production. The method incorporates three aspects, which include product inspection, process inspection, and inspection analysis (Sinha, 2019). Product inspection involves the assessment of the final product to ensure it complies with the set standard for quality, whereas process inspection ensures that the machines, equipment, ad raw materials used in the production process comply with the standard quality. The above aspect not only saves wastage of material by preventing process bottle necks but also ensures the manufacture of quality commodity. On the other side, inspection analysis involves the assessment of both product and process inspection, which aids the manufacturer to identify the exact faulty points in manufacturing process. Generally, inspection has three stages, which include input, work-in-progress, and final product inspection.

SQC involves the use of statistical techniques, such as probability, sampling, and graphs to evaluate and control the quality of product. The method is mainly used in continuous process industries and mass production process; besides, it incorporates a set of methods for ongoing procedures, system, and outcomes (Toledo, Lizarelli, & Santana, 2017). There are three steps involved in SQC, which include analysis of samples, control charts, and corrective measures. Analysis of samples depends on the sampling techniques used, whereby a population of interest is identified and a sample representing the population is drawn and analyzed. Among, the various methods of sampling both simple and stratified random sampling are the most appropriate in drawing a representative sample.

The results of any statistical analysis are efficiently represented in a graph or chart use control charts. There are various graphical methods or tools that aid in the analysis of a given dataset, such as a scatter diagram, Pareto chart, control charts, and frequency plots (McClintock, 2016). Among the above, Control charts tend to be the most effective tool for SQC since they comprise of two charts, the X-bar chart and R-chart The control charts are drawn through the following steps; measuring the characteristics of the sample, computing the mean and standard deviation of the sample, and plotting of the data in reference to the mean and standard deviation. Notably, the control charts can be drawn using the SQC software, such as excel, SPSS, minitab, and STATA, among others (Gejdoš, 2015).

Statistical Quality Control

The measures are entered into SQC software whereby both various descriptive statistics are computed. Notably, the descriptive statistics, particularly the mean and standard deviation are used in computing both the lower and upper control limits (standard units on either sides of the mean) that are essential in creating an X-bar chart. The chart can be utilized to monitor or evaluate the manufacturing process. Besides, the software can be used in  creating another QC chart known as the R chart that monitors whether the process is under control and forecast the variation. (Gejdoš, 2015). The last step of SQC, corrective measure involves the identification of points and causes of deviation thus enables the manufacturer to adopt measure to control the quality of the product.

As evident, the company involves in the production of batch quantities of small components for local industry. Moreover, the company has received a request for 200 Hounsfield Test Pieces in various specification. Therefore, as the control manager one should decide what measurements, strategies, and analysis the company should carry out to calculate the process capability index for the machines.

It has come to my notice that we have received a request for approximately 200 Hounsfield Test Pieces in numerous material specifications. As our company policy states “Quality and durability are ensured” it is our mandate to provide not only quality but also durable products to the clients. Therefore, an effective quality control method will be used in ensuring the batch conforms to the policy. Among the two QC methods the company will adopt the SQC technique since it involves statistical analysis and interpretation of results. Notably for the technique to provide adequate results, there three process that will be incorporated, which include descriptive statistics, statistical process control (SPC), and acceptance sampling.

The descriptive statistics will be used to expose the quality characteristics and relationships, which include average, range, standard deviation, and distribution of data. SPC will aid in inspecting a random sample of the Hounsfield Test Pieces from the company’s production unit and decide whether the manufacturing process in producing products with characteristics that fall within the requested customer specifications. Consequently, acceptance sampling will randomly assess a sample of Hounsfield and justify if it is prudent to accept the entire lot based on the results (accepting or rejecting the products).

As exhibited, there are various measurements of Hounsfield Test Piece, which include internal and external diameter and length. However, the above measurements have been summarized by the cross-sectional area of the product, which is approximately 20mm2. Therefore, to assess if the products conform to the set standards (quality) the cross-sectional area of a random sample of the products will measured. Since the customer requires a total of 200 Hounsfield, the sample will incorporate the 50 pieces, which will aid in generating the descriptive statistics and determining the acceptance sampling.

AQL = 2% LTPD = 5%

Producer risk = 5% Consumer risk = 10%

Let the acceptance number (c) = 1

Proportion Defective (p)


Probability of c































Therefore, at 1 acceptance number, the single sampling scheme of the 200 batch will incorporate 40 units.


Gejdoš, P. (2015). Continuous Quality Improvement by Statistical Process Control. Procedia Economics and Finance, 565-572.

McClintock, T. (2016). Tools and Techniques Useful in Quality Planning, Assurance, and Control. Global Knowledge.

Sinha, D. (2019). Quality Control (QC): Definition, Importance and Tools of Quality Control. Retrieved from Your Article Library Website:

Toledo, J. C., Lizarelli, F. L., & Santana, M. B. (2017). Success factors in the implementation of statistical process control: action research in a chemical plant. SciELO Analytics, 47-54.

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