Design Plan And Diagram Strategies For Competency-Based Assessment

The process we follow is known as competency-based assessment. This means that evidence of your current skills and knowledge will be measured against national standards of best practice, not against the learning you have undertaken either recently or in the past. Some of the assessment will be concerned with how you apply your skills and knowledge in the workplace, and some in the training room as required by each unit.

The assessment tasks have been designed to enable you to demonstrate the requirements of the performance criteria and knowledge in this unit to successfully demonstrate competency at the required standard. 

Your assessor will ensure that you are ready for assessment and will explain the assessment process.  Your assessment tasks will outline the evidence to be collected and how it will be collected, for example; a written activity, case study, or demonstration and observation.

The assessor will also have determined if you have any special needs to be considered during assessment. Changes can be made to the way assessment is undertaken to account for special needs and this is called making Reasonable Adjustment.

Competency-Based Assessment Process and Standards

Design plan and diagram strategies is to enable design to work, the purposes of which can be vacillated, anyway they may join expanding key bits of learning or unique basic substances realizing more complete courses of action in order to achieve better experiences for customers with things, organizations, conditions and structures they rely on. Learning, for this circumstance, this is clear and significant examination of a condition through arrangement techniques, hence understanding the interior thought of things normally.( Vicente, K.J., 2010) The accompanying are a portion of the plan, research and examination strategies used to create a customer's solution.

Uniqueness – Investigating possible results and confinements of obtained conditions by applying fundamental thinking through emotional and quantitative research systems to make new perception of the issue space toward better arrangement courses of action. ( Vicente, K.J., 2010)   

Change – Reclassifying points of interest of plan courses of action which can incite better principles for standard and contemporary blueprint works out.

Joining – Prototyping possible circumstances for better arrangement courses of action that incrementally or basically upgrade the at first obtained situation.

Maintainability – Dealing with the path toward researching, reconsidering and prototyping of plan game plans determinedly after some time.

Enunciation - the visual connection between the parts and the entirety.

a.Continuous improvement

b.Problem solving and decision making

c.RCA, FMEA, DRBFM and Pareto analysis

1. The Continuous improvement applies the concept for the “Plan,do,check and act”. (Suzaki, K., 2014) Suggested that the plan stage is the the stage which involves the planning  and ideas used for improvement, the objectives  and the set policies to make the planning.

The do stage involves the training, and awareness through communication and then implementing the whole idea to escape the possible problems.

The check process involves the monitoring and the analysis actions to results and the corrective controls to achieve the desired outcome.

The act is the final process  where the plan is reviewed and new goals are strategized.

b.Problem solving and decision making

Referring to (Suzaki, K., 2014), when the issue still appears to be overpowering, separate it by rehashing stages until the point that you have portrayals of a few related issues. It causes an incredible arrangement to check your concern investigation for consulting with an another person. When working with different problems,  the problem with high effects should be given the first priority and handled first.

c.RCA, FMEA, DRBFM and Pareto analysis

Pareto - is a factual system in basic leadership utilized for the determination of a predetermined number of errands that deliver huge generally speaking impact.

FMEA -  is a well ordered approach for distinguishing every single conceivable disappointment in an outline, an assembling or get together process, or an item or administration.

Design Plan and Diagram Strategies for Customer's Solution

DRBFM - is a technique used to assess proposed changes to a current outline. It was created by Tatsuhiko Yoshimura, working with Toyota Motor Corporation. It utilizes a worksheet displayed after the FMEA worksheet however the two strategies are not indistinguishable. (Suzaki, K., 2014).

According to (Brans, J.P. and Vincke, P., 2013) computer simulation packages is the proliferation of the conduct of a framework using a computer to recreate the results of a numerical model related with said framework. Simulated purposes include: they are used optimizing performance like engaging engineering ,testings, videos and testing in education.

Design simulations  allow framework originators to examine an issue at a few distinct levels of deliberation thus understanding it to the highest level best.

They also furnish clients with down to earth criticism when outlining true frameworks.

Design simulations brings down the cost of item improvement

Helps the capacity of plan reenactment to lessen the advancement lifecycle and empower the item to achieve the market speedier means less clients will be left baffled.( Baker, R.J., 2008)

Referring to (Baker, R.J., 2008),It is very hard to interpret and come up with a perfect interpretation of a design moden. It leads to assumptions in most cases.

It is very expensive to conduct a successful simulation due to high costs incurred.

It is expensive to design a simulation model

Physical simulations

According to (Sugumar, R.A., 2009),The physical simulations is used in the learning process using the simulation objects to engage the objects of the simulation to extreme vigorous stage.

Interactive simulation or ‘human in the loop’ simulations

These refers to the simulations which interact with human one on one. for example;  when learning how to drive and fly an helicopter

Computer architecture simulation

This is a bit of programming for demonstrating computer  gadgets to anticipate yields and execution measurements on a given info. An engineering test system can demonstrate an objective microchip or whole computer  framework including a processor, a memory framework, and Input and Output gadgets.( Sugumar, R.A., 2009)

Training simulation

The training simulation is used in learning to explain how a certain machine works. This helped the learners to have the skills in handling the real machinery.

Business performance

Alluding to (Sugumar, R.A., 2009)The business performance simulation is used to explain how E-commerce is conducted. This improves the learner’s experience on trust and the intangible nature of the process.

Plant or process design

Simulations help engineers identify any loop hole in the units of the design process. (Sugumar, R.A., 2009)This allows them to take the appropriate choice in the design of the plant

Simulations and Modeling Techniques for Design Process

Linear and non-linear

A linear model is dependably a polynomial of degree 1. They generally frame lines; in different measurements, they may likewise shape planes  or hyperplanes. T heir shape is in every case flawlessly linear, without any bends of any sort while Nonlinear models are significantly harder to understand and control. Illuminating a linear framework with a million communicating factors is extremely possible with a Computer, and most nonlinear solvers wouldn't get even near that.( BlLLINGS, S.A. and Voon, W.S.F., 2013)

Deterministic and stochastic

In deterministic models, the yield of the model is completely controlled by the parameter esteems and the underlying conditions while in Stochastic models have some characteristic irregularity. A similar arrangement of parameter esteems and introductory conditions will prompt a troupe of various yields.( BlLLINGS, S.A. and Voon, W.S.F., 2013)

Steady-state and dynamic

A dynamic model effectively anticipated the profluent convergences of both unstable and non?volatile need poisons from an expansive mechanical wastewater treatment plant.( BlLLINGS, S.A. and Voon, W.S.F., 2013) A steady?state demonstrate, which was figured with the indistinguishable rate conditions and variable influent information, was deficient for dynamic expectations.

Lumped and distributed parameter models

The components fabricating a lumped model are thought of being amassed at particular focuses in space while the components in distribute frameworks are thought of being dispersed in space, with the goal that physical amounts rely upon both time and space, ( Vicente, K.J., 2010).

Continuous and discrete

(Bertsekas, D.P., 2009), discrete event proliferation is fitting for structures whose state is discrete and varies at particular time point and after that residual parts in that state for a long time.

Continuous simulation is appropriate for structures with a steady express that movements tirelessly after some time. Such a structure can be depicted by differential conditions. This is a system to light up these conditions numerically

Deterministic and stochastic

In deterministic models, the yield of the model is completely dictated by the parameter esteems and the underlying conditions.

Stochastic models have some characteristic irregularity. A similar arrangement of parameter esteems and starting conditions will prompt a gathering of various yields.

This tends to imply that on the off chance that you run a reenactment twice, the test system doesn't exit amongst runs thus the following arrangement begins from the past arrangement. In the event that you have a circuit with different stable working focuses, there's no assurance that the outcomes will be the same. Additionally if the outcomes just contrast by numerical resistances.( Bertsekas, D.P., 2009)

OOPM simulation

speaks to a usage for a recreation framework that is under development, and in light of an expansion to question arranged design.it enable investigators to reenact physical procedures by building multimodels.

State variables, constants and random variables

A state variable is one of the factors used to portray the condition of a dynamical framework.

Constant variable is the one whose esteem can't be changed once it has been doled out an esteem

Random variable a variable whose conceivable qualities are numerical results of an irregular marvel,

Inputs, outputs and decisions variables

Input variables are  factors of creation input that can't be changed in the short-run. A factor of generation input that relies on the level of creation. Variable sources of info change contingent on the amount we deliver

Output variables makes it conceivable to store the estimation of a content variable for use after a call closes, without setting up an information activity, (Petrov, V.V., 2012. )

Decisions variables are the factors in a direct program that are an arrangement of amounts that should be resolved keeping in mind the end goal to take care of the issue

By assessing the action based administration and evaluating the last model from the distinctive reproductions as for the normal estimation of the yield variable and oversaw improvement to influence the activity to happen.( Madsen, H., 2013)

Matching CIM with modelling techniques - The intention in the decision of the procedure demonstrating strategies is that they are generally utilized in depicting tricky circumstances in associations.

References

Vicente, K.J., 2010. Cognitive work analysis: Toward safe, productive, and healthy computer-based work. CRC Press.

Suzaki, K., 2014. New manufacturing challenge: Techniques for continuous improvement. Simon and Schuster.

Brans, J.P. and Vincke, P., 2013. Note—A Preference Ranking Organisation Method: (The PROMETHEE Method for Multiple Criteria Decision-Making). Management science, 31(6), pp.647-656.

Baker, R.J., 2008. CMOS: circuit design, layout, and simulation (Vol. 1). John Wiley & Sons.

Sugumar, R.A., 2009. Multi-configuration simulation algorithms for the evaluation of computer architecture designs.

BlLLINGS, S.A. and Voon, W.S.F., 2013. Correlation based model validity tests for non-linear models. International journal of Control, 44(1), pp.235-244.

Bertsekas, D.P., 2009. Network optimization: continuous and discrete models (pp. 467-511). Belmont: Athena Scientific.

Petrov, V.V., 2012. Sums of independent random variables(Vol. 82). Springer Science & Business Media.

Madsen, H., 2013. Parameter estimation in distributed hydrological catchment modelling using automatic calibration with multiple objectives. Advances in water resources, 26(2), pp.205-216.