All 14 entries tagged Rdm
April 22, 2013
Making good decisions is an iterative process. It is a skill that although uses analytical tools it can require some time to learn. It would be very useful to reflect on the decision making process and methods to understand what went wrong to avoid it and what went right to keep it. By continuously following this process the human decision capabilities can improve.
This is important as those analytical skills require practise to be performed in a competitive level. Moreover, with reflection the decision maker can become aware of personal preferences, heuristics and biases.
In my work we keep a log of snags using a software as a part of lessons learned. It would be very useful to document the decision making process to allow the department not just to gain knowledge on how a certain fault is rectified but to record how robust decisions and analyses are carried out to meet the system operations objectives in terms of decision making.
April 21, 2013
Simulation is a very useful decision making tool, yet a complex one. There are multiple softwares to select from and the most accessible is add-in on Excel. Depending on the application the approach can differ. for example, if the management wants to understand the consequences of multiple decisions, experiments can be carried to visualise their results and compare them or if a component performance was needed a CAD software can be used to analyse the performance needs.
although it can be a complicated process and it is not a decision tool on its own, it gives management and decision makers a deep insight to the situation to allow more objective analysis of the decision alternatives.
In my current job, simulation is very useful to carry out product design by using a software such as solid works or autocad. i can analyse what is the needed factor of safety when deciding on the optimal design for a certain component.
Linear programming is a very useful decision tool when the decision is made from few alternatives but when a decision space exists. For instance, when a production plant wants to understand what is the optimal combinations of products. However, it is important to know that linear programming is only suitable where objectives and constraints are linear. If not, it would be an application of operational research to use non-linear programming possibly.
This is a very useful management tool to use the decision objectives to minimise cost or maximise profit by optimising the decision objective.
In my career, linear programming is a very useful tool especially redesigning a mechanical component to be optimised. For example, minimising a product weight can be the design objective which can be given by management to meet a certain strategic objective and specifying stiffness as the design constraint. This can optimise the component design to achieve the desired decision objective.
The selection of a decision method is not a straight forward approach. There is no tool selection reference document to select the most suitable from and it is possible to find more than one suitable tool for a single decision. However, there are few guiding points such as, amount of information available, timescale, complexity, knowledge of the environment and knowledge of various tools.
The knowledge of various tools benefits, applications and shortcomings can aid the process of selecting the most suitable tool for a certain decision.
When i am in a position to make a decision i can start by identifying what are the affecting factors in terms of information, timescale and knowledge of the current problem. Secondly, i can compare the decision objectives to the decision tools available while being aware of their limitations. It is also possible to use multiple tools to cover for certain limitation or multiple objectives.
Using a decision making process is very effective to avoid decision conclusion. Depending on past experience or intuitive judgement is not sufficient. People that does not follow a structured approach can end up focusing on aspects that are not part of the decision. The use of a decision process gives the decision maker a chance to focus on identifying the exact decision problem, identify the decision requirements or constraints and specifically identify the needed decision objectives.
This approach to decision process is very useful as it eliminates the possibility of deviation from the main decision problem. Moreover, this allows for selecting a decision tool that significantly contribute to the decision objectives. Furthermore, in the event of implementing a decision alternative that does not meet the requirements it is possible to track where things went wrong as everything should have been structured and documented.
When facing a system failure in an engineering asset, following a structured approach will focus the use of trouble shooting to develop decision problem, especially if the problem was reoccurring. Moreover, by identifying the decision requirements and objectives, as an engineer i can identify the machine constraints and needs. From there it would be possible to use fault tree analysis or QFD to go further to rectification.
Grid analysis is a tool that allows ranking a decision alternative based on its performance in regards to a certain performance criteria. However, there are certain issues when ranking alternatives. People can rank factors based on personal preference or compensatory heuristics. Preparing qualitative data can reduce dependence on intuition to make an objective decision.
Making an objective decision is very important to reach to a quality decision. Moreover, this focus and depth in analysis can demonstrate the robustness of a decision as the performance criteria are quantitatively measured. Any variation and robustness can be further identified by sensitivity analysis.
At work, This tool is very useful when developing various modifications. if multiple modifications for a machine are developed, GA can help in identifying how each modification perform in the machine various performance criteria. By using technical measures it would be useful to identify the optimal modification based on its overall performance.
April 16, 2013
AHP is a decision tool that analytically rank decision alternatives based on its performance in certain factors. There are few points to focus on when undertaking a decision using AHP. First, when ranking factors during paired comparison it is useful to understand the factors in terms of achieving the strategic objectives to rank them objectively. Secondly, when ranking the factors in terms of a certain alternative it is useful to have qualitative data of how the alternative perform to continue making decisions objectively.
Using qualitative data and considering strategic objectives puts the goal desired by the decision in mind which limits dependence on personal preference, bias and deviation. This can lead to a more objective decision.
In maintenance environment, corrective maintenance is essential and the use of AHP can allow prioritising snags. Ranking objectively can allow our department to meet departmental strategic objective. There is a tendency to close snags that are preferred by the engineer or can be done fast. However, this does not guarantee that it is what the department needs to meet the overall organisation objective. By linking the strategic objective to rank what is needed and use qualitative data to assess the situation can help make objective decision on distributing tasks as the organisation need to perform.
April 14, 2013
The decision tree analysis tool is used to understand the consequences of a decision in numerical terms. However, this decision can be way in future and while time passes evaluation of circumstances can change as the decision point comes closer views become clearer. Moreover, it has to be taken into consideration that a decision tree analyse the decision consequence for a specific period of time while if this period is changed the overall decision can change, hence, time scaling and sensitivity analysis should be taken into consideration.
Having an overall of the decision tool capabilities, limitations and bias possibility is important to have an overview of where the decision will be leading. This awareness allows the decision maker to understand the tool limitation to cover for it by another decision tool and check for the decision validity during progress to decision.
As an engineer this will help me understand the financial consequences of the team technical decisions. Moreover, in new product development it will be beneficial to revisit the decision tree after provisional decision to understand what changes in market demand and strategic objectives have happened and how it can affect the product development decision financially.
March 11, 2013
Measuring the decision quality is an important part of decision knowledge. The quality is not always measured by the decision outcomes as the amount of factors are way complicated in real life business to be considered totally. Measurement cannot depend on qualitative data as interpretation can vary significantly.
The measurement of decision quality allows tthe decision makers to lean assesing decision for more robust decisions. It is also a learning curve which allows the decision maker to improve with experience when usin the appropriate theory and tools.
I can assess the quality of decisions i have to make by examining wide range of alternatives, understand all the objectives and decision requirements, understand associated positives and negatives and assess the possibility of decision implementation. This will allow me to to make an informed decision by measuring its quality before agreeing to it as the most robust decision can be out of the decision list.
In our presentation we considered production location using 2 analysis tools; decision tree and AHP. We also made the most effective media channels for advertisements. In location selection my judgement urged me to select Exmouth due to higher production rate. However, The decision tree demonstrated that in year 1 Exmouth is probably more profitable and in year 2 Lymington is more profitable and has no risk associated. This taught me that judgement is poor without support. Moreover, choosing a robust decision is more effective as plans can go forward without worrying about success rate and fluctuation.
In my career, when trying to think of a solution as an engineer cutting edge solutions can be rewarding but decision analysis might differ the opinion which can allow me to make a more robust and stable decision.