For a company to perform well, high quality production should be embraced and taken into consideration. The objectives set by the company should be related to the quality policy so as to achieve the highest competitive advantage which is an image of the company.
Quality engineering involves the activities that a company uses to ensure that the quality of products and services produced in their company meets the required standards. It mainly deals with quality control and quality assurance management which are the main components in quality engineering (Taguchi, et.al, 2005).
Quality control involves steps intended to ensure that the products or services are being produced as per the set qualities or as per the customer requirements; quality assurance on the other hand is defined as the procedures set to ensure that products/service under production meets the set requirements.
There are some of the techniques used by quality control in ensuring customer needs are met and they include: benchmarking, Deming’s points, and continuous quality improvement. Benchmarking involves a company comparing their performance with another company who might be ahead of them and trying to “copy” what they do to achieve higher performance.
Deming in his argument states that high quality products causes high productivity and lower costs hence the company achieves a greater market share. High quality production means there is less re-doing of work, few mistakes, few/no delays in delivering the products and hence better use of time and materials. Deming’s points has helped the company know its continuous objective and has enabled it strive to improve production systems.
Continuous quality improvement is a quality control method used to ensure quality of products and services is greatly improved and maintained and that solutions to all possible causes of product defects are looked into.
Quality assurance (Prados, et.al, 2005) uses tools like failure testing, statistical process control, and total quality management to ensure products under production met the required standards. Statistical process control is a method used to monitor and control production; it helps in ensuring efficient production with less waste.
The origin of quality engineering has been progressing since early 1920s during the onset of production of quality control practices in Japan. Some contributors like Deming, Juran in United States also started implementing this idea later in 1940s and 1950s.
Deming started quality engineering by using statistical methods for ensuring quality control of the production and this happened during the Second World War. He came up with fourteen point (Chiarini, 2011) plans to help the organization understand the concept of success and these points included breaking down the barriers between departments, managers learning their work and being conversant with leadership skills, improvement of ways of working and production and establishing ideas to help in self- improvement and learning.
Benchmarking being a technique of studying another company who performance is high was being used to aid planning of ideas in the company and it has greatly progressed to date as this helps in building the company’s competitive advantage which brings higher production.
Continuous improvement of quality was started back in 1962 by the Japanese. It involves policies of introducing changes in a business to help in improving its quality. It assumes that the employees in the organization does well and are able to identify ideas for improvement.
Quality circles were developed to help identify better improvements and this involved a team of volunteers in the organization who meet on regular basis to deliberate on the possible problems affecting the quality of their production and try to come up with solutions.
Failure testing forms a crucial part of production process as it ensures that the product or service being produced will not fail under any circumstances. Continuous process of failure testing helps to ensure production is improved.
Statistical quality control practices were started back in early 20th century. They are practices which aid in monitoring and controlling production in an organization (Montgomery, 2007). It was used by the United States during the Second World War in the manufacturing of war devices and it was used by the military in inspection and monitoring production of rifles.
Total quality management is a management practice which started in 1950s and has progressively grown. It involves continuous improvement of production of products and services by combining quality and management tools hence increasing profits of the company and reducing loss. It was originally used in manufacturing sectors but its growth has caused it to be embraced in other operations and public sectors (Akao, 2004).
Total quality management brings together all organizational functions so as to meet customers’ needs and deliver the objectives of the organization.
According to Deming, the key to good quality products and services depends on how the customer is served and the feedback from the customers and for this to be achieved, there are ways which forms the basis of total quality management and they include: ensuring good quality is the leading aspect in achieving organizational objectives, getting feedback from the customers as this dictates the quality level of the products and services in the organization, satisfied customers improves the performance of the company, ensuring that there is no wastes or re-work in production as this reduces production, embracing change on daily basis to improve on the performance, managers and employees should be dedicated to working and also the workers should be empowered in learning new ideas so as to be competent in their production.
After the Second World War, Japan was left in a bad situation and it needed to re-build its way of production and find a way to counter the reputation that their products were of low quality. They started finding solutions on quality improvement and learning what other countries do to improve on quality of their production. They found Deming and Juran who made influence on Japan bad quality processes.
Different ideas were used by the two foreigners and they include; training all personnel in the organization on quality management, monitoring their progress, formation of quality circles to help in monitoring and controlling quality of the production and involving all functions of the organization in the process of quality improvement.
This process helps the company know their level of performance as compared to other companies. It allows an organization to make plans on how to make improvements with the aim of increasing performance. It is divided into different types of benchmarking which include product, performance, process, financial, strategic, and functional benchmarking (Rolstadas, 2013).
There are steps followed to achieve a good benchmarking and they include: finding out your problems, get to know other companies with same processes, find out the leading organizations in your surroundings, visiting their organizations to find out their practices, comparing the practices and implementing/improving the practices.
Quality improvement has grown gradually and there are methods which were developed to help improving the quality, the plan-do-study-act method which was developed by W. Scherwart and it shows how a manager continuously identifies problems and finds solutions (Lewis, 2016). .
There are steps which should be followed to achieve a continuous quality improvement and they are as follows; creating a team with knowledge of what needs improvement, state a clear aim, know the needs of those served by what is to be improved, find out strategies that enable success, discuss the possible changes to aid improvement, plan, collect and use information to allow a good decision making and then implement the best method to make changes.
Another method used to improve quality is the use of control charts to help identify process variation over a long time. They are used to show when a process is in/out of control and hence used as a tool for making continuous quality improvement by reducing the variation.
Flowcharts and bonefish diagrams has also been used to depict continuous quality improvement, they help in finding out a problem hence find the cause and the solution.
A good approach to failure testing should be specific to an industry like manufacturing processes like lean/six sigma that include this testing as part of its approach to production process management (Tian, 2005). Each product has a way of failure and analysis of various failures helps the managers know the impact of the product failure.
Different organizations (Mead & Stehney, 2005) like National institute of Science and technology, American Society for testing and materials states the standards which should be used while testing the failure of a product and service like ISO/IEC 17025 standard.
It helps in controlling and monitoring production and the most effective tool is the use of control charts as it helps in recording of all information and enables one to see when an unusual event happens.
Another tool used is the acceptance sampling and is used ensuring the good quality of finished product. It was developed in Bell Telephone Company (Montgomery, 2009). It involves selecting samples from the produced products and thereafter testing and evaluating them to find out if they meet the correct standards.
The cause and effect diagram (Tseng, 2009) is also used as a statistical tool to monitor production as it helps in showing the cause of variations in the quality of the product. It deals with improvement in materials, processes, equipments and measurement to ensure good quality production.
Tools involved in quality management include; process maps which involve determining who does every activity in the production network. Another tool is the force field analysis which helps in determining the level of difficulty in making change.
Root cause analysis involves finding out the major cause of defect in the product through a series of questions. Cause and effect diagram is another tool which helps in examining factors that lead to a given situation.
The plan-do-check-act cycle (Taylor, et.al, 2013) is also a tool used to bring emphasis in the new change; it involves carrying out tests and checking on the effects and in the end come up with a result to show what has been learned.
Prioritization matrices are tools used to help an organization select tasks with much priority as per the set criteria. They help the company ensure that all factors are implemented and decisions made.
Activity network diagram includes a range of tools used in planning a good program of completing a complex project; they include Gantt Charts and pert charts (Ryan, 2011). .
There has been great development of quality engineering since early 20th century. Many contributors have made a positive impact on the whole topic of quality engineering and adding more valuable information on the approach of work. Standards to guide quality of work produced has been set from the early years and improvements are still going on.
The biggest change in the early years is the improvement of quality through introduction of statistical methods from United States to Japan by Deming.
Another milestone is the advancement of topics in quality engineering which relates to signal to noise ratio and design of performing experiments, this helps in elimination noises during production.
In the 1990s there was creation of ISO 9000 standards (Beck & Walgenbach, 2005) to guide companies in their production as they have to produce as per these standards.
Quality engineering can be traced from manufacturing sector where top engineers utilize concepts of statistical packages and statistical methodologies to enhance production process so as to produce quality products that will meet consumers list of preferences. In the last 10 years, engineers have discovered how statistical methodologies can be applied to manufacture and produce quality products in the field of engineering (Taguchi, Chowdhury & Wu, 2005). In that case, these methodologies have been applied to forecast the type of engineering structures that need to be considered as final products.
This paper review key aspects that can be applied within quality engineering. The paper suggest how various tools have managed to advance quality engineering as well as how quality engineering need to evolve so as to attain significant trends in the field. In the past, a lot of people viewed quality engineering as a set of theories used in production, in making strategies for quality improvement, reliability in manufacturing sector as well as in productivity. According to American Society for Quality (ASQ), the basic issue addressed in ASQ relates to quality engineers (Ryan, 2011). It tend to emphasize deeply on manufacturing as the main pillar of quality engineering. Nevertheless, a lot of complicated, very crucial as well as contemporary challenges need to be reviewed so as enhance adaptability of basic tools within quality engineering. It is very important to note that the future of our field rely heavily on classic quality engineering tools so as to mitigate challenges facing the entire field of engineering.
For the last 20 years, many developing countries have been pressured on issues relating to manufacturing. This has made many quality engineers to shift to industrialized counties where the rules and regulations relating to manufacturing and quality engineering are well spelt out in the labor laws. However, the future of quality engineering face several problems that need to be addressed (DeVor, Chang & Sutherland, 2007). There is conflict of interest between practioners needs and academic research. In that connection, practitioners need academicians so as to focus challenges faced by practioners especially in quality engineering as it evolve to meet the requirement in all application field. Thus, in summary, this paper aim at building bridges between practioners and academicians so as to improve on quality engineering.
In the past statistical control tools were used in monitoring the production, not in the current state, control charts and other tools are used to control and improve production.
There is improvement in statistics modeling because a lot of variables (Bersimis, et.al, 2007) are put into consideration to find out a problem and find a solution to it.
The more complex work is managed using computer systems because of its complexity. Technology has made quality engineering to improve due to innovation of different engineering software tools. There are numerous tools to design structure in the field along with other tools in manufacturing of quality products in engineering sector (Montgomery, 2009). A lot of training in modern technology is being offered to quality engineers so as to make them compatible with modern production and manufacturing in engineering work. Therefore, the current trend in quality engineering relate to productivity improvement of manufacturing and processing industries by application of different manufacturing tools such as lean manufacturing tools.
Lean tools are used in engineering to facilitate manufacturing process by removing the waste as well as to remove overburden at engineering workshops. Lean tool is applied together with SWOT analysis model to promote productivity, over-processing, overproduction as well as to ease motion in engineering field (Tseng, 2009). The wastes to be considered in engineering works include transportation, over-processing, overproduction, waiting, extra processing, inventory, defects and motion.
There are a lot of tools designed currently to enhance quality engineering (Chiarini, 2011). These tools include cellular manufacturing, just in time (JIT), Kanban, production smoothing, total production maintenance (TPM), continuous improvement , 5s, value stream mapping, SMED, line balancing and takt time.
From different reviews gathered from different papers, we summarize by saying successful implementation of lean manufacturing systems will promote quality engineering at current production and in the future.
Conclusion
Quality engineering is best known as statistical and organizational process used to detect a problem in a product and come up with a solution. It has grown greatly since its inception from the need to improving quality to setting up of standards to govern the production. There is still need of improvement as days goes by and as technology improves.
References
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