
PPMP20009 Control Charts and Process Mapping Assignment Sample
Task
Quality control tools for Lean Rashid
Q5. (4 marks)
Discuss how you might use TWO (2) lean quality control tools in the context of the selected project.
Ensure your response is specific to the details in your case study and provide examples or scenarios when the lean quality control tools are used. You should include any assumptions to facilitate your choice (500 words)
In the context of a 24/7 AI chatbot, two lean quality control tools that could be used are Control Charts and Process Mapping.
Control Charts: Control Charts is a tool that helps monitor process performance over time and identifies if any special cause variations are occurring. For the 24/7 AI chatbot, a control chart can be used to monitor key metrics such as response time, accuracy, and customer satisfaction (Chakraborti & Graham 2019). This will help to detect any abnormal behavior in the chatbot's performance and identify the root cause of the problem.
For example, Control Chart Example: In a 24/7 AI chatbot customer service scenario, a control chart can be used to monitor the accuracy of the chatbot's responses over time. The control chart would track the percentage of correct responses given by the chatbot, and provide a visual representation of the performance (Golilarz et al 2019). The chart would also indicate any trends or patterns, and highlight any significant changes or fluctuations in the accuracy of the chatbot's responses. For example, if the chart shows that the accuracy of the chatbot's responses has dropped significantly, the team can investigate the cause of the problem and make improvements, such as updating the chatbot's training data or fine-tuning its algorithms. The control chart helps to ensure that the chatbot is providing consistent, accurate responses and quickly identify and address any performance issues.
Process Mapping: Process Mapping is a tool that helps visualize the flow of work and identify bottlenecks and areas for improvement. For the 24/7 AI chatbot, process mapping can be used to understand the flow of the conversation between the customer and the chatbot (Al-Fedaghi & Mohamad 2019). This will help identify areas where the chatbot is struggling to understand the customer's request or provide a relevant response.
For example, imagine that a customer service chatbot is being developed for a retail company. To use process mapping, the team could create a flowchart that outlines the steps the chatbot takes to respond to a customer query. This might include the chatbot's initial greeting, its ability to understand the customer's request, the steps it takes to access relevant information from the database, and the final response sent to the customer (Abideen & Mohamad 2021). The process map would highlight the different stages of the customer interaction, and any potential bottlenecks or areas where the chatbot struggles to respond effectively. The map could be used to identify any process improvements that could be made to improve the customer experience, such as providing additional training data or fine-tuning the chatbot's algorithms.
Histogram – Histogram is also one of the graphical representations of data based on the frequency distribution. Histogram has been used to analyse and obtain whether the data has been normally distributed or not and determined outliers. This has been done by separating the range of gained values based on the counting’s and intervals. Also, it counts how many values have fallen into each and every interval. Using this, it is easy to see variation of data. On the other hand, this helps to assess whether the processes are stable or not during the working process (isixsigma, 2022).
For the AI project for ISS call response, the use of histogram helps to spot the problem exactly where the problem occurs. By this, it is easy to obtain effective solutions easily and quickly. In addition, it helps to save money and time by permitting everyone in the project an enhanced production process with direct access.
For example, the AI implementation is looking at high cost, and if particular activity of technology implementation is higher than normal, then it is assumed to be there was an error with the system and activities. The histogram will analyse and determine the activity distribution to each resource along with the cost of activities.
Solution
Discuss how you might use TWO (2) lean quality control tools in the context of the selected project.
In the context of a 24/7 AI chatbot, two lean quality control tools that could be used are Control Charts and Process Mapping.
Control Charts: Control Charts is a tool that helps monitor process performance over time and identifies if any special cause variations are occurring. For the 24/7 AI chatbot, a control chart can be used to monitor key metrics such as response time, accuracy, and customer satisfaction (Chakraborti & Graham 2019). University Assignment Help, This will help to detect any abnormal behavior in the chatbot's performance and identify the root cause of the problem.
For example, Control Chart Example: In a 24/7 AI chatbot customer service scenario, a control chart can be used to monitor the accuracy of the chatbot's responses over time. The control chart would track the percentage of correct responses given by the chatbot, and provide a visual representation of the performance (Golilarz et al 2019). The chart would also indicate any trends or patterns, and highlight any significant changes or fluctuations in the accuracy of the chatbot's responses. For example, if the chart shows that the accuracy of the chatbot's responses has dropped significantly, the team can investigate the cause of the problem and make improvements, such as updating the chatbot's training data or fine-tuning its algorithms. The control chart helps to ensure that the chatbot is providing consistent, accurate responses and quickly identify and address any performance issues.
Process Mapping: Process Mapping is a tool that helps visualize the flow of work and identify bottlenecks and areas for improvement. For the 24/7 AI chatbot, process mapping can be used to understand the flow of the conversation between the customer and the chatbot (Al-Fedaghi & Mohamad 2019). This will help identify areas where the chatbot is struggling to understand the customer's request or provide a relevant response.
For example, imagine that a customer service chatbot is being developed for a retail company. To use process mapping, the team could create a flowchart that outlines the steps the chatbot takes to respond to a customer query. This might include the chatbot's initial greeting, its ability to understand the customer's request, the steps it takes to access relevant information from the database, and the final response sent to the customer (Abideen & Mohamad 2021). The process map would highlight the different stages of the customer interaction, and any potential bottlenecks or areas where the chatbot struggles to respond effectively. The map could be used to identify any process improvements that could be made to improve the customer experience, such as providing additional training data or fine-tuning the chatbot's algorithms.
Assumptions:
1. The chatbot is a rule-based chatbot that uses predefined responses to answer customer queries.
2. The chatbot is integrated with a database that stores customer interactions and metrics.
3. The chatbot is hosted on a cloud infrastructure that is scalable and reliable.
By using these two lean quality control tools, the performance of the 24/7 AI chatbot can be monitored and improved continuously. Control Charts will help identify any abnormal behavior and provide early warning signs, while Process Mapping will help understand the flow of the conversation and identify areas for improvement. By continuously monitoring and improving the chatbot, customer satisfaction can be increased, and downtime can be reduced, resulting in a better overall customer experience.
References
Abideen, A., & Mohamad, F. B. (2021). Improving the performance of a Malaysian pharmaceutical warehouse supply chain by integrating value stream mapping and discrete event simulation. Journal of Modelling in Management, 16(1), 70-102. http://digilibft.unla.ac.id/repository/JTI.EMER.2021.014.pdf
Al-Fedaghi, S., & Mohamad, Y. (2019, November). Business process mapping: a case study. In 2019 IEEE/ACS 16th International Conference on Computer Systems and
Applications (AICCSA) (pp. 1-8). IEEE. https://www.researchgate.net/profile/Sabah-Al-Fedaghi/publication/339976981_Business_Process_Mapping_A_Case_Study/links/5ff1b17092851c13fee31f24/Business-Process-Mapping-A-Case-Study
Chakraborti, S., & Graham, M. A. (2019). Nonparametric (distribution-free) control charts: An updated overview and some results. Quality Engineering, 31(4), 523-544. https://www.tandfonline.com/doi/pdf/10.1080/08982112.2018.1549330?needAccess=true&role=button
Golilarz, N. A., Addeh, A., Gao, H., Ali, L., Roshandeh, A. M., Munir, H. M., & Khan, R. U. (2019). A new automatic method for control chart patterns recognition based on ConvNet and harris hawks meta heuristic optimization algorithm. Ieee Access, 7, 149398-149405. https://ieeexplore.ieee.org/iel7/6287639/8600701/08859191.pdf
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