Various improvement methods are used which are discussed.
Brainstorming
Brainstorming is a technique to systematically generate ideas usually to handle a challenging situation, from a group of people by nurturing free-thinking. There are several such opportunities in any organisation, e.g. Improving productivity, increasing sales, finding new business development areas, launching new products or defining new processes.
While there may be well defined techniques or processes to handle these situations, but brainstorming is a critical activity in all of these processes. Techniques such as Affinity, Nominal group technique, Cause and Effect Diagram, Failure mode effect analysis, 5 whys, Fault tree analysis, Decision matrix, and Risk analysis require brainstorming as an integral part of their execution. The list is endless!
Brainstorming required for generating inputs for the above techniques is complex as compared to the free flow ideation that one usually associates with the term brainstorming. An example of the kind of brainstorming required here can be observed in a 5-why analysis, where brainstorming occurs for every why in a hierarchical manner until a root cause is discovered.
Brainstorming session must be orchestrated by a facilitator. The number of participants in a session must be limited to a manageable number – typically between 5 and 15. There are few rules for a successful brainstorming, which should be enforced by the facilitator. These rules are listed below.
- Focus on generating a large number of ideas
- Active involvement of every participant in the process
- Encourage out-of-the-box thinking and creativity
- Promote criticism free environment – encourage all types of ideas including wild or seemingly ridiculous ideas while keeping the purpose of the brainstorming in mind
- Combine ideas to create newer ideas
- Setup a reasonable time limit based on the challenge in hand
Process to conduct brainstorming is as
- Select and block a (lively) room free from interruptions and distractions for brainstorming.
- Identify and invite the participants. The invite must clearly state the purpose of brainstorming.
- Before the start, ensure that the room is equipped with basic essentials like blackboard, flipcharts, pens, and large size post-its, etc.
- Initiate the session by clearly explaining the purpose, possibly already written and highlighted on the board. Also set the basic rules for the session. Set some time towards the end of the session for organizing the ideas generated.
- Invite people to come up with ideas. One of the participants may be designated to record each idea or alternatively each participant may be requested to pen his/her idea on a post-it to speed up the process. Maintain a lively environment, monotony must be avoided at every cost.
- Ensure that the rules of a successful brainstorming are followed properly.
- Towards the end, focus on organizing ideas and eliminating the duplicate ones. If the number of ideas generated is sufficiently large, affinity diagram may be used to organize the ideas.
- Close the session with a note collectively appreciating each ones contribution.
5 Whys
To use the 5 Whys tool, you select an identified cause of defects and ask “why” five times. You may ask a lot more than just five “why” questions, but asking “why” five times per cause is a good rule of thumb. If you start a root cause analysis and you’re only going down two or three levels, you’re probably still just getting at the symptoms of the problem and not the true root cause. The goal for moving through root cause analysis using the 5 Whys and other tools is always to get down to the actual, actionable, true root cause. If you eliminate the root cause of defects, the defects will disappear. They are asked in a sequence from top to bottom for root cause analysis, as
- Why 1: Select a cause and ask “Why does this problem exist?”
- Why 2: Look for possible sources of the cause
- Why 3: Eliminate improbable causes
- Why 4: Identify probable root causes and analyze them
- Why 5: Identify the actual root cause and solve the issue
An example of a manufacturing process with a defect is considered for 5Whys, as
- Why did the defect occur? Could the cause be the inconsistent flow of the input material?
- If it is the inconsistent flow of the input material, why did that occur?
- If the cause is an incorrect measurement, why did that occur? Maybe the measuring tools are giving inconsistent readings.
- Why are the measuring tools giving inconsistent readings? Perhaps the measuring tools are incorrectly calibrated.
- Why are the measuring tools incorrectly calibrated? The cause could be that there is no measurement system in place.
The root cause would then be that there is no measurement system in place.
Multi-vari studies
Multi-Vari Analysis is a tool that graphically displays patterns of variation. These studies are used to identify possible X’s and/or families of variation. These families of variation can frequently hide within a subgroup, between groups or over time.
It is a technique for viewing multiple sources of process variation. Different sources of variation are categorized into families of related causes and quantified to reveal the largest causes. Multi-vari analysis provides a breakdown for example, that machine B on shift 1 is causing the most variation. It won’t quantify the variation just show where it is. Multi-Vari is the perfect tool to determine where the variability is coming from in process (lot-to-lot, shift-to-shift, machine-to-machine, etc.), because it does not require to manipulate the independent variables (or process parameters) as with design of experiments. It enables analyzing the effects of multiple factors, multi-vari analysis is widely used in six sigma projects.
Also, the effect of categorical type inputs can be displayed on a response on a multi-vari chart. It is one of the tools used to reduce the trivial many inputs to the vital few. In other words it is used to identify possible Xs or families of variation, such as variation within a subgroup, between subgroups, or over time. Multi vari charts are useful for quickly identifying positional, temporal and cyclical variation in processes.
FMEA
The acronym FMEA stands for “Failure Modes and Effects Analysis”. It represents a technique aimed at averting future issues in project processes and eliminating risks that may hamper a solution.
It identifies and evaluates defects which could potentially result in reducing quality of a product. Defects within the methodology are defined as anything that reduces the speed or quality at which a product or service is delivered to customers. FMEA is used to discover and prioritize aspects of the process that demand improvement and also to statistically analyze the success of a preemptive solution. There various types of FMEA are
- System FMEA – Used to analyze complete systems and/or sub-systems during the concept of design stage.
- Design FMEA – Used the analyze a product design before it is released to manufacturing.
- Process FMEA -Used to analyze manufacturing and/or assembly process.
The steps to creating a FMEA are
- List the key process steps in the first column usually from the Cause & Effect Matrix.
- List the potential failure mode for each process step.
- List the effects of this failure mode.
- Rate how severe this effect is with 1 being not severe at all and 10 being extremely severe. Ensure the team understands it.
- Identify the causes of the failure mode/effect and rank it as the effects in the occurrence column but, the name implies the score for how likely this cause will occur.
- Identify the controls in place to detect the issue and rank its effectiveness in the detection column. Here a score of 1 would mean we have excellent controls and 10 would mean no controls or extremely weak controls.
- Multiply the severity, occurrence, and detection numbers and store this value in the RPN (risk priority number) column. This is the key number that will be used to identify where the team should focus first.
- Sort by RPN number and identify most critical issues.
- Assign specific actions with responsible persons.
- Once actions have been completed, re-score the occurrence and detection.
Measurement system capability re-analysis
It is a method to re-identify the components of variation in the measurement. It is used to re-quantify the impact of measurement errors and to ensure the integrity of data used for analysis.
Just as a process has inherent variations, the process of measurement has variations too. Therefore, when making decisions that relies on data, it is important to ensure that the systems that collect that data are accurate and precise. Although it may not be possible to totally eliminate measurement errors, the objective of it is to ensure that measurement variance is relatively much smaller than the observed variance. It uses scientific tools to determine the amount of total variation is from the measurement system.
The areas of measurement error are analyzed and quantified
- Accuracy / Bias – The difference from the true value and the value from the measurement system. Accuracy represents the closeness to a defined target.
- Resolution / Discrimination – The goal is to have at least 5 distinct values or categories of readings. The lack of resolution will not allow a measurement system detect change.
- Linearity – It examines the performance of the measurement system throughout the range of measurements.
- Stability – It is analyzed using control charts. Ensuring the measurements taken by appraiser(s) for the process is stable and consistent over time.
- Repeatability & Reproducibility (Gage R&R) –
- Reproducibility is the ability of one appraiser to get the same result and another appraiser or the ability of all appraisers to get the same results among each other.
- Repeatability – It is the ability for an appraiser to repeat his/her measurements each time when analyzing the same part, unit, etc. In destructive testing (such as tensile testing) these reading will not be possible and some statistical software programs have options to select for destructive testing.
Post-improvement capability analysis
Post improvement re-measuring and re-analyzing the capability and performance of a process under review enables organizations to numerically represent and interpret its current state, and to report its sigma level. When done correctly, process capability analyses enable project team to precisely assess current performance in light of future goals, and ultimately, to determine the need and targets of process improvement. Process capabilities can be determined for normal and non-normal data, and for variable (continuous) and attribute (discrete) data alike. It is reported through the statistical measurements of Cp, Cpk, Pp, and Ppk which are
- Cp= Process Capability. A simple and straightforward indicator of process capability.
- Cpk= Process Capability Index. Adjustment of Cp for the effect of non-centered distribution.
- Pp= Process Performance. A simple and straightforward indicator of process performance.
- Ppk= Process Performance Index. Adjustment of Pp for the effect of non-centered distribution.
It also involves validating solutions through F-test, t-test and other similar tests.