amit kumar shukla

A top-down diagram, also known as a hierarchical diagram or tree diagram, is a visual representation that illustrates the structure and hierarchy of a system or project. It starts with a main concept or goal at the top and breaks it down into smaller, more detailed components or subtasks as you move down the diagram.
In a DMAIC (Define, Measure, Analyze, Improve, Control) project, a top-down diagram can be a useful tool in several ways:
1.       Project Planning: At the beginning of the project, this diagram can be used to plan and define the major phases and task involved in each phase of the DMAIC methodology. It helps provide a high-level project structure and helps ensure that all necessary steps are considered. This also helps to define all Toll gate of project with time line.
2.       Task Breakdown: As the project progresses, can be used to break down each phase and each task by DMAIC methodology into more specific tasks or subtasks. This helps in organizing and prioritizing the work with role and responsibility and timeline tracker.
3.       Visual Management for Communication: A top-down diagram provides a visual representation of the project structure, making it easier to communicate the overall plan and progress to stakeholders, team members, or other project participants. Example Google Sheet with Dash Board - It helps ensure everyone has a clear understanding of the project's hierarchy and the relationships between different tasks or components.
4.       Identifying Dependencies: The hierarchical nature of a top-down diagram can help identify dependencies between different tasks or phases in a DMAIC project. It allows you to visualize the relationships and dependencies between various activities, ensuring that they are properly sequenced and coordinated.
5.       Problem Analysis: In the Analyze phase of DMAIC, a top-down diagram can be used to break down the problem or issue into its underlying causes and factors. By analyzing the problem hierarchy, you can identify the root causes and focus on addressing them systematically.
6.       Prioritization and Resource Allocation: By breaking down the project into its components and subtasks, a top-down diagram can help prioritize tasks based on their importance and urgency. It enables better resource allocation by highlighting critical areas that require more attention or resources.
7.       Risk Management: A top-down diagram can be used to identify and assess risks associated with different components or phases of the DMAIC project. By analyzing the diagram, potential risks and their impact on project outcomes can be identified, allowing for proactive risk management.
8.       Change Management: When implementing improvements during the Improve phase of DMAIC, a top-down diagram can be used to assess the impact of changes on various components of the project. It helps in planning and managing the transition from the current state to the desired improved state.
9.       Documentation: A top-down diagram serves as a visual documentation of the project's structure and progress. It can be included in project reports, presentations, or documentation to provide a clear overview of the project's hierarchy and accomplishments.
Overall, a top-down diagram serves as a valuable tool for planning, organizing, and communicating the structure and progress of a DMAIC project. It helps ensure that all necessary steps are accounted for, facilitates effective teamwork, and assists in problem analysis and solution implementation.
 

Evolutionary Operation experiment: EVOP is SPC technique is used for industrial settings to improve the system performance- optimizing – operation conditions.
The method is helping to us making incremental changes of system input variables and Impacting on output. Again monitoring the output, and then select best combination of variables to get best output. The process is repeated process on based on real time, with the goal of continuously improving the system's performance.
Implementing an Evolutionary Operation experiment Method
1.       Define the problem: Clearly define the problem that for solution. This required process or system optimize and identifying the objectives and constraints
2.       Identify the factors: Identify the factors that affect the performance of the process or system. Example process parameters, machine setting, raw material specification, Parts specification etc.
3.       Define the experimental design: The experiment should be designed in such a way that it can show the main effects of the factors and any interactions between the factors
4.       After that we need to carry out experiment. This will involve running the process or system under different combinations of the factors and measuring the performance.
5.       After the experiment is completed, we need to analyse, which factor have maximum impact on performance of the process or system.
 
6.       Optimize the process: Based on the results of the analysis, we can implement required change for best process or system to optimize its performance.  Example Part specification / tolerance, RM change/ machine parameter
7.       Verify the results: After required changes – need to verify result of process/ system.
 
Advantages:
1.       EVOP - Identifying and reducing the variability in the process, resulting in improved process efficiency.
2.       Can be implement without using complex machine/ software
3.       Cost effective solution for process optimization as compare to other approach
4.       EVOP- Output- High Quality product
5.       EVOP process gives quick result for process optimization.
Disadvantages:
1.         The EVOP lengthy process. if the process has multiple input variables than process requires multiple iterations
2.         EVOP Limited used : it is suitable to improving a single process, and it may not be effective for complex systems with interdependent processes.
3.         Process complexity: EVOP not sutable for complex process
4.         Limited applicability: EVOP may not be effective for processes with low variability.
5.         Limited precision: EVOP may not provide precise results as it relies on trial and error testing, and the optimal solution may not be reached.
Evolutionary Operation example
Appliance Manufacturing Example
Issue: 10% of machine is rejected due to clamping Pressure and line speed
>>As per mgf process process – we find out there are 2 process parameter which are more critical for Process rejection Clamping Pressure Kg/cm2 & Line Speed cm/sec. Let us take trial run 1,2,3 as per below table and % rejection of each trial

>>Trial 4th condition will be:  3rd Trail+2nd trail – 1st trial. Then Pressure will be 10.4 and time 60sec and rejection rate 6%

>>by similar method - Trial 5th , 6 & 7th trial result are here

Finally we got best conditions are Clamping Pressure 10.7 Kg/cm2 & Line Speed 40 cm/sec & 0.1% rejection.