In any engineering process, the control objectives are always to ensure system stability, consider the factor of safety, utilize minimum time in the manufacture or development of a given product, ensure total conformity to the required standards, fully meet the varying customer needs and save on the overall running production costs. To satisfy all these control engineering strategies, adequate precautionary measures need to be formulated to ensure accuracy and preciseness of the engineering processes so as to minimize any errors within the system.
Various control systems incorporating the Six-Sigma models have been put in place in order to help in the identification and elimination of production errors. This approach measures the total number of defects in a particular process and devises methods to counter the occurrence of such defects. This approach is said to be cost effective if applied in the correct way, under guidance of highly specialized personnel.
In general terms, Six Sigma is regarded as a measure of the total number of defects in a particular operation or process. Developed in 1981 by USAs Motorola Company, the business management tool enjoys broad-based applications in various sectors and industries such as engineering, manufacturing, business administration, customer service, quality assurance, research and development, inspection and testing, shipping, purchasing, healthcare, environmental management etc (Geoff, 2001).
The Six-Sigma approach of problem solution revolves around identifying defect opportunities in the aforementioned processes taking into consideration several variables such as associated errors and defects occurring on a given assembled part, the approximate number of points where the defect can occur, and a thorough examination of individual production stages to minimize occurrence of defects at each stage (Harris, 2008).
Six -Sigma incorporates several quality management tools and statistical methods to establish a particular infrastructure that fully meets the organizational needs. In order to guarantee the stability of any Six-Sigma project undertaken by an organization, defined steps with measurable targets are followed in a logical sequence. The measurable quantities or control strategies in this domain include but are not limited to maximization of profits, reduction of costs, or increase the safety standards of the engineering process (Jiju, 2008)
The Origin of Six- Sigma
The six-sigma process traces its origins from the perception that if there exists at least 6 standard deviations amid the nearest specification limit and the process mean, then all items within the process unit will meet the required specifications (Geoff, 2001). This argument is strongly supported by mathematical modeling formulas used in control engineering dynamics and other process stability studies. Capability studies as applied to control engineering processes measure the total number of normal variations (standard deviations) in sigma units.
If the standard deviation of a process rises due to the dynamics involved, it causes the process mean to shift further from the tolerance center. As a result, less normal variations end up fitting between the nearest specification boundary and the mean, thus minimizing the sigma number and raising the probability of parameters outside the specification (Geoff, 2001).
Six-Sigma in Distribution Systems
In the broad engineering arena, there exist quite a number of distribution systems which may incorporate the use of the six sigma models. Some of the traditional engineering fields where this model is applicable include commercial and industrial power distribution systems in electrical engineering, pneumatic systems as applied to in instrumentation engineering, process monitory, supervision and data acquisition as applied to control engineering, telemetry and frequency modulations applied in telecommunication engineering among other fields.
The Six-Sigma model is a statistical ideology to variability or unevenness representation of a given set of data or information gathered about its own average. This approach is only applicable to data that conforms to the normal distribution curve as shown below.
In this regard, approximately 66 percent of the data falls in one Sigma of the mean, 96 within two, 99 percent within three and 99.999 within four. The rate of error or defect for any process having a capability of 4 sigma is said to be 3 per 50, 000. In as much as this error margin sounds negligible, it may have serious negative repercussions on any engineering process (Lloyd Holsenback, 2006).
On interpretation of this statistical information, a potential repercussion may be portrayed in the power transmission and distribution systems, i.e. the chances of defects in form of power outages occurring after every six months could be approximately ten thousand. By incorporating the Six-Sigma approach in the power transmission and distribution systems, the frequency of power outages and associated electrical faults would be minimized greatly. Out of one million defect opportunities in any system using the Six-Sigma model, only 3.4 errors are deemed to occur.
In engineering, the main objective of adopting the Six-Sigma model is generally to improve the overall quality of the processes in question by minimizing the rate at which errors and associated defects occur. Over the years, defects in form of outages, power surges due to transient high currents and short circuiting have posed a serious challenge to the field of electrical and power engineering. These defects often arise in the power transmission lines and are often accompanied by several negative effects e.g. fires, destruction of property and electrocution of unsuspecting consumers. Power outages on the other hand lead to business losses and inconveniences to the economic sectors that wholly depend on electrical energy (Sutherland, 2001).
The Six-Sigma approach can be used effectively in addressing such problems in order to ensure quality and reliability. This control strategy may play a critical role in identifying the various elements that affect the quality and stability of the process before optimizing in order limit process variations and minimize failure rates and steady-state errors. Control and supervisory measures can then be put in place to guarantee system stability and systemize the power transmission networks.
Requirements for Incorporating the Six-Sigma Approach
Initiating the use of various Six-Sigma models within any given distribution channel bring along various benefits to a given organization ranging from improved profitability, increased competitiveness and optimal running costs.
Traditional engineering processes designed by engineers for various purposes such as production, instrumentation, modeling, measurement and manufacturing can easily be rendered obsolete if and if they remain limited to the actual industrial processes (Reidenbach and Goeke, 2010). To avoid such scenarios, engineers have to expand their horizons beyond their normal job description and try to understand and internalize the workings of distribution systems, value creation and understanding, and use their ingenuity in incorporating customer definitions and requirements. For this model to be successfully incorporated, several measures ought to be put in place in order to maximize the returns. Such requirements include-
Enhancing the nature of relationship between the dealers, manufacturers and other stakeholders. This is based on the fact that all the stakeholders involved at one point within the distribution channel play an essential role in value addition of the products or services in question. Optimal Six-Sigma models require maximum cooperation from all the players involved.
For any complex engineering process, the Six-Sigma approach or methodology followed should be such that it minimizes all risks, in a cost effective manner that guarantees the safety and health of the engineers and the end user, should ensure that the quality of the product match with the required standards, and finally, the process should be environmentally friendly. These requirements may be tested andor certified by running computer simulations of the Six-Sigma programs before actual implementation.
Thorough understanding of the precise value as specified or required by the consumer or end user of the products or services resulting from a given engineering process. In this perspective, all systems within a distribution channels have to be aligned in the most efficient and effective manner in order to guarantee value. Suggestions and recommendations from the end user have to be incorporated in the Six-Sigma models of problem solution.
Application of suitable metrics in order to ensure the efficiency an appropriate value delivery structure. This may be achieved by changing the firms competitive value plan and monitoring these changes to ensure conformity to the Six-Sigma concepts.
It is also a requirement that value streams are mapped across the organizational boundaries putting into consideration the prevailing market conditions and customer satisfaction.
When these requirements are not fully satisfied in the preliminary stages of six-sigma incorporation, the process in question may fail to yield the desired results. According to Kreitner Kinicki (2003), there are many factors that lead to the failure of many six sigma projects. The main factors in this case include poor leadership structures, inadequate support from the senior management staff, ineffective communication and communication breakdowns, incompetent personnel with little or no knowledge concerning the six-sigma tools, establishing a project that is not viable, with no clear definition. Another possible cause of failure may be attributed to individual attitudes concerning the six-sigma project, resistance to change due to fear of job losses, and the cultural element of human response to change. From this perspective, any organization wishing to incorporate the six-sigma approach in problem solution should be prepared to encounter several challenges and obstructions that may fully hamper the process (Pexton, 2007). It may therefore take a relatively long period before the expected results are yielded after using the six-sigma approach.
Implementing Six Sigma
The implementation of Six-Sigma projects within any organization or any engineering system always encounters several challenges. Its incorporation may however be achieved through outsourcing from independent consultancy firms that offer Six Sigma services or by introducing its concepts into every personnels job, with assistance or facilitation from a few, highly specialized individuals. The second approach helps in the development of a workplace culture where commitment to excellence andor quality is pervasive (Eckes, 2003).
Team work is highly cherished in the implementation of Six-Sigma projects within an organization. The team may comprise of control engineers and other engineers drawn from other fields, communicators, data experts, process specialists, and end users or customers who in most cases define the product value or quality.
Six-Sigma may also be implemented by following the DMAIC methodology which takes shape in five phases namely problem Definition which takes into account customer requirements and the ultimate goals of the engineering process, Measurement of the essential aspects of the existing process and collecting relevant data, data Analysis to establish the cause effect relationship, by investigating the existing weaknesses in the method and considering other factors, carrying out process optimization or Improvement based on the results of the data analysis. Optimization may be through experimental designs, trouble shooting and mistake proofing, in order to minimize steady-state errors and ensure system stability.
The final implementation phase is the Control of future processes. This may be done through process automation that tends to detect and correct any errors within the process. Such control engineering systems may include human-machine interface software, SCADA statistical programs for supervisory control and data acquisition, visual workplaces etc (DeFeo and William, 2005). The DMAIC implementation approach is used in the improvement of existing engineering processes to match the changing technology.
When designing a new engineering process, to be used in the development of new products the DMADV approach is used in the implementation. In this methodology, it is a requirement that the process Defines the design objectives, in tandem with enterprise strategy and customer requirements, Measures clearly identifies all the characteristics that may influence the product quality, stability of the production process and product capabilities, putting into consideration all the risks involved. The next implementation phase is to Analyze the various design alternatives by looking at their respective costs of implementation, approximate time for the implementation, efficiency among other factors.
This analysis helps in the selection of the best approach in the design before embarking on the actual Design process which may involve computer aided designs and optimization processes. The final phase using the DMADV approach is the Verification process which may require setting up of pilot runs, implementation of the engineering process, testing and safety certification and commissioning of the final process or products implemented through the Six-Sigma approach (DeFeo William, 2005). This approach is also referred to as the Design For Six Sigma (DFSS).
From the discussions, it can be seen that Six-Sigma is an engineering and business management strategy that utilizes statistical tools in establishing the root causes of a given problem with an aim of suggesting optimal solutions to the identified problems andor challenges. Most processes which have incorporated the six-sigma tools have almost reached perfection with minimum or no errors and defects in the production line. If the Six-Sigma management tool is adopted by any firm, the business ends up improving its competitiveness and overall profitability in a given sector.
For engineering processes, defects and production errors ought to be eliminated at all times. The Six-Sigma approach therefore helps in achieving this objective. The impacts caused by errors or defects in the production andor engineering distribution process are in most cases costly, dangerous and even life threatening.
Some of the dangers that Six-Sigma approach seeks to eliminate in engineering include short-circuiting, electrocution, fires, explosions due to instrument failure, deaths due to failure of medical instrumentations e.g. the life support machine, and general business losses resulting from such errors. Looking at it from this domain, all engineering processes should incorporate the Six-Sigma tools at various stages in order to ensure safety and quality of the products, in addition to environmental management and health of the users.
Various control systems incorporating the Six-Sigma models have been put in place in order to help in the identification and elimination of production errors. This approach measures the total number of defects in a particular process and devises methods to counter the occurrence of such defects. This approach is said to be cost effective if applied in the correct way, under guidance of highly specialized personnel.
In general terms, Six Sigma is regarded as a measure of the total number of defects in a particular operation or process. Developed in 1981 by USAs Motorola Company, the business management tool enjoys broad-based applications in various sectors and industries such as engineering, manufacturing, business administration, customer service, quality assurance, research and development, inspection and testing, shipping, purchasing, healthcare, environmental management etc (Geoff, 2001).
The Six-Sigma approach of problem solution revolves around identifying defect opportunities in the aforementioned processes taking into consideration several variables such as associated errors and defects occurring on a given assembled part, the approximate number of points where the defect can occur, and a thorough examination of individual production stages to minimize occurrence of defects at each stage (Harris, 2008).
Six -Sigma incorporates several quality management tools and statistical methods to establish a particular infrastructure that fully meets the organizational needs. In order to guarantee the stability of any Six-Sigma project undertaken by an organization, defined steps with measurable targets are followed in a logical sequence. The measurable quantities or control strategies in this domain include but are not limited to maximization of profits, reduction of costs, or increase the safety standards of the engineering process (Jiju, 2008)
The Origin of Six- Sigma
The six-sigma process traces its origins from the perception that if there exists at least 6 standard deviations amid the nearest specification limit and the process mean, then all items within the process unit will meet the required specifications (Geoff, 2001). This argument is strongly supported by mathematical modeling formulas used in control engineering dynamics and other process stability studies. Capability studies as applied to control engineering processes measure the total number of normal variations (standard deviations) in sigma units.
If the standard deviation of a process rises due to the dynamics involved, it causes the process mean to shift further from the tolerance center. As a result, less normal variations end up fitting between the nearest specification boundary and the mean, thus minimizing the sigma number and raising the probability of parameters outside the specification (Geoff, 2001).
Six-Sigma in Distribution Systems
In the broad engineering arena, there exist quite a number of distribution systems which may incorporate the use of the six sigma models. Some of the traditional engineering fields where this model is applicable include commercial and industrial power distribution systems in electrical engineering, pneumatic systems as applied to in instrumentation engineering, process monitory, supervision and data acquisition as applied to control engineering, telemetry and frequency modulations applied in telecommunication engineering among other fields.
The Six-Sigma model is a statistical ideology to variability or unevenness representation of a given set of data or information gathered about its own average. This approach is only applicable to data that conforms to the normal distribution curve as shown below.
In this regard, approximately 66 percent of the data falls in one Sigma of the mean, 96 within two, 99 percent within three and 99.999 within four. The rate of error or defect for any process having a capability of 4 sigma is said to be 3 per 50, 000. In as much as this error margin sounds negligible, it may have serious negative repercussions on any engineering process (Lloyd Holsenback, 2006).
On interpretation of this statistical information, a potential repercussion may be portrayed in the power transmission and distribution systems, i.e. the chances of defects in form of power outages occurring after every six months could be approximately ten thousand. By incorporating the Six-Sigma approach in the power transmission and distribution systems, the frequency of power outages and associated electrical faults would be minimized greatly. Out of one million defect opportunities in any system using the Six-Sigma model, only 3.4 errors are deemed to occur.
In engineering, the main objective of adopting the Six-Sigma model is generally to improve the overall quality of the processes in question by minimizing the rate at which errors and associated defects occur. Over the years, defects in form of outages, power surges due to transient high currents and short circuiting have posed a serious challenge to the field of electrical and power engineering. These defects often arise in the power transmission lines and are often accompanied by several negative effects e.g. fires, destruction of property and electrocution of unsuspecting consumers. Power outages on the other hand lead to business losses and inconveniences to the economic sectors that wholly depend on electrical energy (Sutherland, 2001).
The Six-Sigma approach can be used effectively in addressing such problems in order to ensure quality and reliability. This control strategy may play a critical role in identifying the various elements that affect the quality and stability of the process before optimizing in order limit process variations and minimize failure rates and steady-state errors. Control and supervisory measures can then be put in place to guarantee system stability and systemize the power transmission networks.
Requirements for Incorporating the Six-Sigma Approach
Initiating the use of various Six-Sigma models within any given distribution channel bring along various benefits to a given organization ranging from improved profitability, increased competitiveness and optimal running costs.
Traditional engineering processes designed by engineers for various purposes such as production, instrumentation, modeling, measurement and manufacturing can easily be rendered obsolete if and if they remain limited to the actual industrial processes (Reidenbach and Goeke, 2010). To avoid such scenarios, engineers have to expand their horizons beyond their normal job description and try to understand and internalize the workings of distribution systems, value creation and understanding, and use their ingenuity in incorporating customer definitions and requirements. For this model to be successfully incorporated, several measures ought to be put in place in order to maximize the returns. Such requirements include-
Enhancing the nature of relationship between the dealers, manufacturers and other stakeholders. This is based on the fact that all the stakeholders involved at one point within the distribution channel play an essential role in value addition of the products or services in question. Optimal Six-Sigma models require maximum cooperation from all the players involved.
For any complex engineering process, the Six-Sigma approach or methodology followed should be such that it minimizes all risks, in a cost effective manner that guarantees the safety and health of the engineers and the end user, should ensure that the quality of the product match with the required standards, and finally, the process should be environmentally friendly. These requirements may be tested andor certified by running computer simulations of the Six-Sigma programs before actual implementation.
Thorough understanding of the precise value as specified or required by the consumer or end user of the products or services resulting from a given engineering process. In this perspective, all systems within a distribution channels have to be aligned in the most efficient and effective manner in order to guarantee value. Suggestions and recommendations from the end user have to be incorporated in the Six-Sigma models of problem solution.
Application of suitable metrics in order to ensure the efficiency an appropriate value delivery structure. This may be achieved by changing the firms competitive value plan and monitoring these changes to ensure conformity to the Six-Sigma concepts.
It is also a requirement that value streams are mapped across the organizational boundaries putting into consideration the prevailing market conditions and customer satisfaction.
When these requirements are not fully satisfied in the preliminary stages of six-sigma incorporation, the process in question may fail to yield the desired results. According to Kreitner Kinicki (2003), there are many factors that lead to the failure of many six sigma projects. The main factors in this case include poor leadership structures, inadequate support from the senior management staff, ineffective communication and communication breakdowns, incompetent personnel with little or no knowledge concerning the six-sigma tools, establishing a project that is not viable, with no clear definition. Another possible cause of failure may be attributed to individual attitudes concerning the six-sigma project, resistance to change due to fear of job losses, and the cultural element of human response to change. From this perspective, any organization wishing to incorporate the six-sigma approach in problem solution should be prepared to encounter several challenges and obstructions that may fully hamper the process (Pexton, 2007). It may therefore take a relatively long period before the expected results are yielded after using the six-sigma approach.
Implementing Six Sigma
The implementation of Six-Sigma projects within any organization or any engineering system always encounters several challenges. Its incorporation may however be achieved through outsourcing from independent consultancy firms that offer Six Sigma services or by introducing its concepts into every personnels job, with assistance or facilitation from a few, highly specialized individuals. The second approach helps in the development of a workplace culture where commitment to excellence andor quality is pervasive (Eckes, 2003).
Team work is highly cherished in the implementation of Six-Sigma projects within an organization. The team may comprise of control engineers and other engineers drawn from other fields, communicators, data experts, process specialists, and end users or customers who in most cases define the product value or quality.
Six-Sigma may also be implemented by following the DMAIC methodology which takes shape in five phases namely problem Definition which takes into account customer requirements and the ultimate goals of the engineering process, Measurement of the essential aspects of the existing process and collecting relevant data, data Analysis to establish the cause effect relationship, by investigating the existing weaknesses in the method and considering other factors, carrying out process optimization or Improvement based on the results of the data analysis. Optimization may be through experimental designs, trouble shooting and mistake proofing, in order to minimize steady-state errors and ensure system stability.
The final implementation phase is the Control of future processes. This may be done through process automation that tends to detect and correct any errors within the process. Such control engineering systems may include human-machine interface software, SCADA statistical programs for supervisory control and data acquisition, visual workplaces etc (DeFeo and William, 2005). The DMAIC implementation approach is used in the improvement of existing engineering processes to match the changing technology.
When designing a new engineering process, to be used in the development of new products the DMADV approach is used in the implementation. In this methodology, it is a requirement that the process Defines the design objectives, in tandem with enterprise strategy and customer requirements, Measures clearly identifies all the characteristics that may influence the product quality, stability of the production process and product capabilities, putting into consideration all the risks involved. The next implementation phase is to Analyze the various design alternatives by looking at their respective costs of implementation, approximate time for the implementation, efficiency among other factors.
This analysis helps in the selection of the best approach in the design before embarking on the actual Design process which may involve computer aided designs and optimization processes. The final phase using the DMADV approach is the Verification process which may require setting up of pilot runs, implementation of the engineering process, testing and safety certification and commissioning of the final process or products implemented through the Six-Sigma approach (DeFeo William, 2005). This approach is also referred to as the Design For Six Sigma (DFSS).
From the discussions, it can be seen that Six-Sigma is an engineering and business management strategy that utilizes statistical tools in establishing the root causes of a given problem with an aim of suggesting optimal solutions to the identified problems andor challenges. Most processes which have incorporated the six-sigma tools have almost reached perfection with minimum or no errors and defects in the production line. If the Six-Sigma management tool is adopted by any firm, the business ends up improving its competitiveness and overall profitability in a given sector.
For engineering processes, defects and production errors ought to be eliminated at all times. The Six-Sigma approach therefore helps in achieving this objective. The impacts caused by errors or defects in the production andor engineering distribution process are in most cases costly, dangerous and even life threatening.
Some of the dangers that Six-Sigma approach seeks to eliminate in engineering include short-circuiting, electrocution, fires, explosions due to instrument failure, deaths due to failure of medical instrumentations e.g. the life support machine, and general business losses resulting from such errors. Looking at it from this domain, all engineering processes should incorporate the Six-Sigma tools at various stages in order to ensure safety and quality of the products, in addition to environmental management and health of the users.
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