Prepare a literature review on the subject of Statistical Process Control, covering the concept from its inception up to the present day.
You will conduct a review of the academic literature on the subject of statistical process control.
Following your review, you are to analyse a given set of data to evaluate the performance of a fictional brewery in a given scenario.
You will be expected to illustrate your discussion with examples from academic journals, the trade press and other authoritative sources.
The word count should be 2000 words ±10% (tables, diagrams and appendices are excluded from the count).
1. Prepare a literature review on the subject of Statistical Process Control, covering the concept from its inception up to the present day.
Ensure that you include references to at least 10 peer-reviewed articles, no more than ten years old. You may also acknowledge older works, providing they are of sufficient importance in charting the development of SPC.
(50% of word count)
2. The supplied spreadsheet contains historic data recording the temperature of combined effluent discharged by a fictional brewery, Waterside Lager Limited (WLL). The data comprises temperatures recorded four times a day over the month of September 2022.
The brewery’s discharges are normally controlled within the range 25oC to 35oC. The maximum legally permitted temperature is 40oC.
Regular maintenance is performed on the balancing system (which neutralises the pH of the effluent at the expense of heating the discharge in the process), normally on a weekly basis.
Use the data to visualise the performance of the effluent control process, describing your analytical approach in detail. Include any graphs generated.
In your view, how well has the plant performed?
What priorities for quality improvements should the plant management set?
(50% of word count)
Please if something not clear let me know to save the time.
The inception of SPC dates back to the early 1920s when Walter A. Shewhart, an engineer at Bell Laboratories, developed the concept of control charts. Shewhart’s work was based on the idea of statistical control, which involves the use of statistical methods to measure and analyze the variability of a process. The first control chart was created in 1924, and it became the foundation of SPC. Shewhart’s work was published in his book “Statistical Method from the Viewpoint of Quality Control” in 1931.
In the following years, SPC gained popularity among industrial engineers as a powerful tool for quality improvement. During World War II, SPC was widely adopted in the defense industry to improve the quality of products, and it contributed significantly to the war effort.
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The 1950s and 1960s saw the development of new statistical techniques for SPC, such as the use of multivariate analysis and design of experiments (DOE). These techniques allowed for the optimization of processes, leading to significant improvements in quality and productivity.
In the 1970s, the Japanese manufacturing industry started to adopt SPC, which became a cornerstone of the Total Quality Management (TQM) philosophy. Japanese companies such as Toyota, Honda, and Sony used SPC to improve their manufacturing processes and gain a competitive advantage in the global market. This led to the development of the Lean Manufacturing philosophy, which emphasizes the elimination of waste and the continuous improvement of processes.
The 1980s saw the development of new software tools for SPC, making it easier to implement and use in various industries. These tools allowed for the integration of SPC with other quality management systems, such as Six Sigma, and contributed to the widespread adoption of SPC in the service industry.
In the 1990s, SPC continued to evolve with the development of new statistical techniques, such as the use of artificial intelligence and machine learning. These techniques allowed for the analysis of large datasets and the identification of complex patterns in the data. SPC also became an integral part of the ISO 9000 quality management system, which requires organizations to use statistical methods to monitor and control their processes.
In recent years, SPC has become even more accessible with the development of cloud-based software tools and the Internet of Things (IoT). These tools allow for real-time monitoring of processes and the automatic generation of control charts, reducing the need for manual data entry and analysis. SPC has also become an important tool for the management of supply chains, allowing organizations to monitor and control the quality of products and services across their entire value chain.
In conclusion, Statistical Process Control has come a long way since its inception in the early 1920s. It has evolved from a simple control chart to a powerful quality management tool used in various industries worldwide. With the development of new statistical techniques and software tools, SPC continues to be a vital tool for improving the quality and productivity of processes in the 21st century.