The global pursuit of higher quality and corporate social responsibility are motivating corporations to set climate preservation goals and to employ quality theory processes, notably lean six sigma methods. One of the significant contemporary social responsibility initiatives is climate preservation. Climate conservation has been dramatically achieved through the increases efficient production of clean energy, such as hydroelectricity and nuclear power plants. However, advanced quality management processes are needed to effectively and safely operate electricity generation plants of any type due to their potential to cause significant man-made accidental disasters if certain critical processes become out of control. This chapter explores how lean six sigma quality theories were applied for risk management at a renewable energy hydroelectricity facility. Quality inspections were collected from a plant in New York, USA. A statistical process control model was developed based on the attribute and continuous inspection data.
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It is important to study how quality theories such as lean six sigma may be used for risk management in the clean energy production sector. Continuous process checking or improvement in electricity generation are needed due to the global pursuit of higher quality and corporate social responsibility (Peinado, Graeml, & Vianna, 2018). Decision makers at energy creation companies are moving in the direction of setting climate preservation goals and to employ quality theory processes, notably lean six sigma methods (Strang, 2017a).
One of the significant contemporary social responsibility initiatives is climate preservation. Climate conservation has been dramatically achieved through the increases efficient production of clean energy, such as hydroelectricity and nuclear power plants. However, advanced quality management processes are needed to effectively and safely operate electricity generation plants of any type due to their potential to cause significant man-made accidental disasters if certain critical processes become out of control (Nersesian & Strang, 2017).
This chapter explores how lean six sigma quality theories were applied for risk management at a renewable energy hydroelectricity facility. Quality inspections were collected from a plant in New York, USA. A statistical process control model was developed in an easy-to-use spreadsheet software package, based on collected attribute and continuous inspection data.
The main contribution of this chapter is to show how lean six sigma was applied in a clean energy manufacturing plant. This may generalize more broadly, globally, to other hydro-electric, wind, solar, nuclear and even fossil-fuel based energy utilities, because lean six sigma is a primarily risk prevention or mitigation methodology not a risk management estimation technique. The lean tools allow a company to detect problems that have occurred not ones that will occur. When a process is out of control the problem has already started. However, it can dramatically reduce subsequent problems at an energy generation plant if problems can be detected early on, so they may be brought back into control. For example, the near-fatal nuclear plant overheating at Three Mile Island in the U.S. was an example of a process out of control, but it was accidentally detected by a diligent employee. By comparison the nuclear explosion disaster in Chernobyl Ukraine was an example of a process out of control that was not detected in time, with catastrophic results. By illustrating how lean six sigma was applied in a simple easy to use spreadsheet application, this may be of interest to all levels of management working at energy production plants, including nuclear, solar, wind, fossil-fuel as well as hydro (like the current study). In other words the risk detection and mitigation approaches in this chapter, namely lean six sigma, should generalize widely to all types of energy creation around the world.