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About Ronaaq

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    McCain foods India
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    Technical Services Manager
  1. Kano Model

    Kano Model:- It was developed by Dr. Noriaki Kano in 1984. It is a very good and effective tool of analysis to find out what are the features that customers want from your product. And how much those features affect customer satisfaction. Below is the table showing what is meaning of the needs mentioned and its impact to customer satisfaction. Basic Need Performance need Excitement Needs Definition These features are the basic requirement of the product/service. Customers expect that these features are already present in the product, and do not ask for these features. These features are those which customer demands. These features are the points on which customer compares product of two companies. These features/needs are those which are not demanded by customers. Many times customers are not aware about these features. Effect on Satisfaction level Enhancing these features may not increase the satisfaction level of the customer. But if the performance of these features drop customers will be highly dissatisfied. Performance of these features will affect customer satisfaction positively as well as negatively. If our product is having these features/needs customer satisfaction increases a lot because they are delighted/excited by these features Effect on Market/Market share These are the features/needs of a product that will help a company to get in the market. If we as company satisfy performance needs we will be able to remain in market. If we want to excel in our market, be world class we should increase these features in our product. Effect of overkill/ over enhancing these features Once a company has reached a satisfaction level for these features company should not try to improve on these features, as improving more than required will add cost to product without affecting customer satisfaction positively. If we want to improve our product’s satisfaction level we need to improve performance of these features. It’s also important to keep in mind that the more functionality we add, the bigger the investment we have to make. We should try to improve on these needs, but keeping the investment minimum, otherwise customer will feel burden of these excitement needs. Graphical presentation In attached graph, you can see that curve for basic need, becomes stable after reaching a satisfaction level. These features do not increase the satisfaction level positively. Curve for performance needs is a linear curve. If these performance of these features is better compared to others satisfaction level increases, but if performance is not good it will affect satisfaction level negatively. Curve for excitement needs, starts on a +ve quadrant, absence of these features will not affect the satisfaction level, but presence of these features highly affect satisfaction level. Other names Threshold attributes, unspoken needs, Must be needs. Linear, One dimensional, satisfying customer needs Delighter, attractive needs. Example:- Mobile Phone Mobile, Charger with USB cable. Headphones, Dual sim/single sim, Memory capacity, warranty period, camera resolution, battery size, cost. Separate camera for group selfie, Free data plan for 1 year, Free One time screen replacement, cover, screen guard, Portable charger. As times passes performance need à basic needs, and excitement needs àperformance needs and new excitement needs arise. Categories of these needs do not remain the same. It evolves along with time. Taking same example of mobile phones. Previously when there were only landline phones, mobile phones ability to call and send messages was an excitement need. But now those two features are part of basic needs with performance needs of battery life, camera quality. At present there are excitement needs for mobile phones such as face detection, group selfie camera, etc. These features which are excitement need at present will become a performance needs in future and new excitement need will arise. Thus shift in the needs continues. Once we know needs of customer for a particular product and their categories. 1. We can make sure that our product has all the basic needs required by customer. 2. We can check which features/needs are redundant and can be removed from the product to save cost. 3. Which performance features required improvement. 4. Check Excitement needs and find a solution to incorporate them with your product. 5. Since there are competitors, this analysis is of great use for development of new product. Kano.pptx
  2. Statistically significant difference means that the two variables that we are comparing are having some difference caused because of some special cause and not because of chance. 1. We can use this analysis to verify whether the changes that are done in the process are actually giving the desired results or it is just random chance. In a company, downtime caused due to Maintenance and electrical problems was 5%, after we have a new maintenance manager; he rolled out a new system of maintenance as a result of that downtime reduced to 3.5%. With this analysis we can statically prove that the reduction in downtime is because of the new process. 2. For measuring one quality parameter, we have two machines. We can use this analysis to check whether testing on type of machine gives different result. From the analysis we can statistically prove that machines does affect the results that we are getting, because the p value is <0.5. 3. Similarly, if for an output Y, we have multiple X. we can also analyze which X are having statistical significant difference. and find the impact of that X with further analysis.
  3. Differentiate between a stable process and a capable process. Is Process Stability supposed to be a pre-requisite for all type of processes? Explain with appropriate examples. Sr.no Stable process Capable process Definition A process which is able to produce the output consistently over a long period of time A process which is able to produce the output meeting customer specification Pre-requisites Customer specification (USL/target/LSL) is not required. Customer specification (USL/target/LSL) is required. Variations It has only common cause of variation. It can have special cause of variation along with common causes. Output predictability over a long period of time We can predict the output over a long period of time Since there are special causes of variation, it will be slightly difficult to predict the output over a long period of time Before going to example, I would like to clarify that a stable process does not mean that it is a capable process and vice versa. Definitely process stability is a pre-requisite for all the type of process. Case study:- A company is producing a product which has a weight of 3Kg. Stable process:- Bellows distribution curve shows that the process is stable, as it is making product consistently at a mean of about 3.002 Kg. Non stable process:- Now over a period of time if there is some special cause of variation, than the same process cannot be stable process. We can get a graph as shown below. We can see from the graph that there are two spikes in the distribution curve, one is near 3000 and another one is around 3025. At the mean value 3012.43 we are getting very few readings. Product should be of 3 Kg, but due to some special cause entire mean after that cause has shifted to 3025. Thus this process is not stable. Capable and stable process:- Now in the same process, when we add customer requirements, we can see whether the process is capable or not. From the below distribution curve we can see that we are getting weight of the product well within specification. This process is both stable and capable. Capable process but not a stable process:- In above distribution curve of weights, we can see that the product is well within specification, but it is not stable. It is very difficult to predict the output of the process. Also minimum value is very near to the LSL. Now if customer revised the specification limits and makes it more stringent. In that case our process will not be capable to meet the requirements. And we may lose the business. Hence it is very important the process is stable. Once we eliminate special causes of variation from the process and make it stable. It becomes easier to adopt new customer requirements. The only thing required will be to shift the mean towards target. As an example if the customer comes up and tells us that he requires a 2.5 kg of product instead of 3 kg. We will have to change the process mean to 2.5 kg and the process will be capable on its own. As we know that the process is stable.
  4. Correlation

    Correlation gives a relationship between two variables. It gives relationship between input X and output Y. It gives a good graphical representation of how the two variables are related. But one cannot determine whether Input X is the cause of output Y. it can be the case that both the variables are X, or both the variables are Y. As an example, Crime rate is increased in Ahmedabad VS Ice cream sales has decreased. There can be good correlation between both the events but, the real root cause can be something different. In Ahmedabad, weather is pleasant in winter, so in winter the criminals become more active and hence crime rate increases while on the other hand since it is cold people prefer hot drinks rather than ice cream. So ice cream sales have decreased. This is a major drawback of correlation. Knowing this most of the people use this analysis. Because it acts as a good start, we can filter out many inputs from the analysis which does not show a relationship with the output Y. This can save a lot of time. Further we can work on root cause analysis , based on the correlation study. We can know which parameter is having how much impact on the output.
  5. VOC:- Voice of customer. VOC is the customer’s expectation/needs from a particular product/process. Customers can be internal/external. Case study:- Product:- ABC of 1 Kg pack size VOC:- Customer specification:- 1. Nett weight:- 1 Kg +/- 10%. USL :- 1100gms LSL:- 900 gm 2. Piece weight 20 gms( +/- 2gms). 3. Piece count:- 47 to 53 in 1KG. It was observed that we were processing, such that each piece weight came about 18 gms. So customer was getting 56 pieces in each bag. We were within limits of VOC. Our internal customer said that we are running at a piece weight of 18 gms which is our LSL, so it should be increased. After completion of project, weight of each piece was maintained at 20 gms, and in each pack of 1 kg we were getting 50 pieces. Product was completely under specification. But we started getting complains, because the piece count decreased from 56 to 50. Customer was getting 6 pieces of product less in each pack. Customer was not happy to see this change, though we were following the specification given by customer. Thus overemphasis on VOC might cost our business in some cases.
  6. Process mapping

    There are various types of process mapping, but we can categorize them in mainly 5 groups. 1. SIPOC 2. High Level Process Map/Flow chart 3. Detailed process Map 4. Swim Lane Map 5. Value steam Mapping SIPOC:- SIPOC stands for Supplier – Inputs – Process – Outputs – Customer · The required inputs (and their providers) are listed to the left, and the key process outputs (and their recipients) are listed to the right. The SIPOC provides a focus for discussion of what the process is all about. · With SIPOC we will be able to know who supplies to process, what is the output of the process? What are requirements of a customer? · It is recommended to have a SIPOC for every project because they are helpful when discussing the process with others and simple to make. High Level Process Maps/High level Flow chart:- It provides an overview of the processes and objectives that drive an organization. The purpose is to provide quick and easy insights into what the process does, without getting into the details of how it’s done. Detailed Process Map/ Detailed Flow chart:- While studying the high level process map, if we want to get more detail of a particular process. We may need to make a details process map for that process. Swim lane Map:- Swim lanes is a technique used in process mapping to simplify the work procedure. The process is divided into several swim lanes. These are represented by the different people that will perform that job. Detailed process maps are often prepared in the swim lane format. This is because often there are multiple detailed process maps. Keeping track of who is supposed to do what may get confusing. Swim lanes help to simplify them. Value Stream Map:- VSMs are typically used in Lean applications. They are rich with information that is useful when planning process improvements. Value Stream Maps are sometimes called Material and Information Flow Diagrams. With value stream map we can see how material is moving from one process to another and how information is flowing. We can also see WIPs and its level. We can get relevant process details such as cycle time, change over time,etc. What is the wait time for information/product can also be gathered from a value stream map. They require more skill to build than simpler process maps, but they provide great information. Below is the summary of various process maps. Process Mapping When It is used SIPOC to get overview of what are inputs/outputs, what are customers’ requirements High level process Map Shows how the process works Detailed process Map To get deep understanding of the process Swim Lane Maps It shows which department is is involved with how much intensity in that process Value stream mapping It is the ultimate process map, which gives all the relevant detail about the process. For me Value stream mapping is the best template to do a process mapping. Now for an organization which is new to these tools, or for an organization which I am not aware of I will follow below sequence of process mapping.
  7. Continuous data is measured and attribute data is counted. There are some cases when we actually count our measurement, but for analysis purpose those data are considered continuous. Below are some examples. Example1:- In a 3 Kg packet of French Fry, we measure count per Kg. which is an attribute data as it is counted. But if we want to check what is the mean and median of count in a 3 Kg pack, we need to consider the same data as continuous. Short text for inspection object Count Per Kg Fries 3 Kg 374.000 Fries 3 Kg 372.000 Fries 3 Kg 376.000 Fries 3 Kg 379.000 Fries 3 Kg 372.000 Fries 3 Kg 372.000 Fries 3 Kg 375.000 Fries 3 Kg 358.000 Fries 3 Kg 369.000 Fries 3 Kg 368.000 Fries 3 Kg 367.000 Count Per Kg Quantiles 100.0% maximum 386 99.5% 383 97.5% 382 90.0% 379 75.0% quartile 376 50.0% median 372 25.0% quartile 367 10.0% 358 2.5% 351 0.5% 347 0.0% minimum 344 Summary Statistics Mean 370.38577 Std Dev 8.0232368 Std Err Mean 0.3696912 Upper 95% Mean 371.11223 Lower 95% Mean 369.65932 N 471 Sum 174451.7 Variance 64.372329 CV 2.1661838 N Missing 476 Example 2:- Similar to above example, for a sample of 1 Kg, we measure critical and major defects. Which again is an attribute data, but for analysis they are considered continuous data. Short text for inspection object Critical + Major + Minor Defects Fries 3 Kg 10.000 Fries 3 Kg 5.000 Fries 3 Kg 8.000 Fries 3 Kg 15.000 Fries 3 Kg 13.000 Fries 3 Kg 14.000 Fries 3 Kg 8.000 Fries 3 Kg 10.000 Fries 3 Kg 2.000 Fries 3 Kg 10.000 Fries 3 Kg 14.000 Fries 3 Kg 9.000 Fries 3 Kg 9.000 Fries 3 Kg 11.000 Fries 3 Kg 10.000 Fries 3 Kg 11.000 Fries 3 Kg 7.000 Fries 3 Kg 8.000 Fries 3 Kg 8.000 Fries 3 Kg 7.000 Distributions Critical + Major Other Quantiles 100.0% maximum 22 99.5% 19.175 97.5% 12.175 90.0% 8 75.0% quartile 6 50.0% median 4 25.0% quartile 2 10.0% 2 2.5% 0 0.5% 0 0.0% minimum 0 Summary Statistics Mean 4.4491525 Std Dev 2.9942548 Std Err Mean 0.1378217 Upper 95% Mean 4.7199741 Lower 95% Mean 4.178331 N 472 Sum 2100 Variance 8.9655619 CV 67.299442 N Missing 475 There are many such data in real life in which measurement is done in counts, but for analysis they need to be considered continuous data. In Summary, it depends a lot on what analysis you want to have for a particular data set. And we should have understanding of what affect a tool will have , if the data are considered continuous or attribute during the analysis.
  8. Sr.no. Correction Corrective Action Preventive action 1 Correction is an action taken to eliminate a detected nonconformity/problem Action to eliminate the cause of a detected nonconformity/problem. Action to eliminate the cause of a potential nonconformity/Problem 2 Correction addresses the short-term need and gets immediate attention. Corrective action is a long-term solution. Preventive action is a Futuristic solution. 3 It is a fire fighting process. Corrective action is a reactive process and it is performed to bring the deviation under control Preventive action is a proactive process 4 For corrections problem has already occurred. For corrective action problem has already occurred. For Preventive Action a problem has not yet occurred 5 Root cause analysis, 5 Whys’s, Ishikawa diagram Failure Mode Effect Analysis (FMEA) or risk management, Fault Tree Analysis. Example:- In this Diwali vacation, you have planned to visit you parents. You are on the way with your wife in your new car. Suddenly you one of your tire is punctured. Now you need to change the tire in your new Diwali clothes. But when you open your trunk you get even bigger surprise that there is no spare tire. Now for above example your correction, Corrective action and preventive action will be as follows. Correction:- Call for help from nearby place and get your tire repaired. Corrective action:- To keep an extra spare tire in your trunk. This will help us when similar problem is repeated. Preventive action:- Before using the car, we should check the basic requirement to run the car. Like, Fuel, tire pressure, spare tire, water level, etc. This is to prevent other possible problem that can come in a car. I think the question about a situation where correction is only desired solution, is a googly. Because I don’t think there is any situation/problem, where you will neglect corrective actions/ preventive actions
  9. Check sheet

    Considering BPM and its various tools are implemented properly, I think check sheets will be removed from the system. But for education of quality it should not be ignored completely, because we must have our basics correct. People should understand how those data are coming from BPM tools.
  10. Kanban / Pull System

    When to go for Push system 1. Push system should be applied to seasonal products where the company can have a small daily capacity but through proper planning and forecasting could ship very large quantities when their product is in high demand. If we apply pull strategies to seasonal products, we can run out of capacity when the demand for that product is high. Other option is to increase manufacturing capacity, but most of the time in off seasons you will not utilize full capacity. 2. Products with small demand uncertainty, as the forecast will provide a good indication of what to produce and keep in inventory. Eventually resulting in lesser lead times. When forecasting is very close to the demand graph, having a push system reduced the lead time drastically. 3. Products with high importance of economies of scale in reducing costs. Some products cost very less when produced in bulk, instead of small frequent orders. 4. When your products are exported, it is better to deal with push system. If we go for pull system, there will be way too many jets and vessels to be booked for transporting your products. 5. When customer is not aware about the products. Example of push marketing can be seen in department stores that sell fragrance lines. The manufacturing brand of the fragrance will often offer sales incentives to the department stores for pushing its products onto customers. This tactic can be especially beneficial for new brands that aren't well-established or for new lines within a given brand that need additional promotion. After all, for many consumers, being introduced to the fragrance at the store is their first experience with the product, and they wouldn't know to ask for it if they didn't know it existed. 6. Push system can be used when the brand loyalty is low. Push system can help in increasing the loyalty, by shifting money used in advertisements and endorsements to improving products and resource allocations. Overall no company will survive solely on Push or pull system, there has to be hybrid of both the systems. Percentage importance of both the system varies from industry to industries.
  11. A false alarm:- Rejecting a good product. As the no. of false alarm increases rework/rejection increases. So it’s a producer’s risk. Most of the producers will be keen on reducing false alarms. It can also be referred as Type 1 error. Missed alert:- Accepting a rejected product. When a bad product is accepted and reaches customer/consumer. It is consumer’s risk. It can also be referred as type 2 error. Which error to be preferred over other depends on the criticality of the product/parameter that is in consideration? In food industry:- there are many parameters that are checked. One of the main parameter is addition of allergen/non allergen ingredients. In this parameter, missed alert will have more impact. As if an allergen product is consumed by a person, it can lead to his death also. Taking one more parameter:- Color of product. If we were not able to produce the product as per target color, and it is off by just a bit. In this case more emphasis is to be given on false alarms. As too many false alarms will lead to rework/rejection.
  12. FTA:- Fault tree analysis A technique by which many events that interacts to produce other events can be related using simple logical relationship. FTA is a technique generally used in reliability and safety analysis. Bell Telephone Laboratories developed the concept in 1962 for the US Air Force for use with the Minuteman system. It was later adopted and extensively applied by the Boeing Company. Fault tree analysis is one of many symbolic "analytical logic techniques" found in operations research and in system reliability. FTA is a Top down approach Fault tree diagrams represent the logical relationship between sub-system and component failures and how they combine to cause system failures. The TOP event of a fault tree represents a system event of interest and is connected by logical gates to component failures known as basic events. Limitation:- 1. Difficult to conceive all possible scenarios leading to the top of event 2. Making an FTA for large system can be tedious, as we will require a separate fault tree for each top event. 3. Fault trees developed by different users are generally different in structure. Which leads to confusion 4. Same event may occur in different part of tree, leading to some confusion. 5. Correlation between basic events are difficult to model and exact solution to correlated event does not exist 6. Subjective decisions regarding the level of details and completeness are often necessary. 7. Can be costly in time & effort
  13. Yes, these 3 questions are sufficient enough to find the value added activities in any industry/process/situation. But at the same time definition of Non-value added activities change. There can be many activities that does not fulfill the three question to be value added but are important for business. Those activities are categorized as NVA but required. There are different names for those NVA , like Business NVA, Supportive NVA, Essential NVA Some examples Inline inspection in any process Preparing some reports Maintaining employees data etc. If we put them under VA activities, than we will be limiting our scope for improvement. People will always think that they are VA so we should not change them All this BNVA, SNVA, ENVA can be reduced or eliminated over the period of time when we change the process or machine. An example of withdrawing money from a bank Few years back, the process of withdrawing money from a bank took about 3-4 hours depending upon the bank and which day you went to bank. 1. Drive to bank àSNVA (15 minutes) 2. Wait in line à NVA (15 minutes) 3. Complete transactionà VA (2 minutes) 4. Banker count the cash à SNVA ( 2minutes) 5. Banker again count the cash àNVA ( 2 minutes) 6. You count the cash àNVA (2 minutes) 7. Drive Home à NVA (15 minutes) Note:- Time taken here are bare minimum. Out of the total of 53 minutes, only 2 minutes are value added, rest of the activities are either Supportive NVA or NVA. Nowadays, with ATM available at every corner of a street, we can withdraw cash in about half an hour. Total time is reduced to 34 minutes. Which gives a saving of 19 minutes. Still, there are some SNVA and NVA in this process. 1. Drive to ATM à SNVA 15 minutes 2. Withdraw cash àVA 2 minutes 3. Count the notes à NVA 2 minutes 4. Drive to HomeàSNVA 15 minutes With online net banking, we can do the transaction sitting at home which further reduced the NVA and SNVA. Thus, in my opinion, those activities for which we have a doubt that they are VA or not they should be categorized as SNVA (Supportive NVA), so that in longer run we can improve upon those.
  14. 5S

    Definitely it does help when we implement 5S outside manufacturing. Steps Meaning/ Tag line How it is useful in outside manufacturing/monetary gain. Sorting Removing unwanted things from a work place “IF IN DOUBT MOVE IT OUT” In an office, too much time is wasted on finding the file that you have been working on. When you search that file in your PC, you will find so many files/folders 80% of those files are of no use. So use the tag line “If in doubt move it out” There will be a lot of time saved by doing this. If we convert a person’s salary into INR/minute. We measure time saved by sorting we can easily calculate the savings due to 1st step of 5S. Taking an average salary of 50,000 INR /month, with 25 working days and a day of 8 hours. We get about 4 INR/minute. Now if a person waste about 30-40 minutes in a day searching for different files, we can save about 3000 INR/day. Set In Order Keeping things near the workplace based on it’s frequency of use “A PLACE FOR EVERYTHING AND EVERYTHING IN ITS PLACE…..” For this step lets take an example of Operation theater in a Hospital. If 5S is not implemented in an operation there, and after a day or two doctors find that one of his Forceps is missing. What will you think about it? J Imagine doctor giving a call to every patient that had undergone operation asking them to get their checkup done immediately to find the missing Forceps. Now in this situation, if a person dies, wecant calculate cost. But if another operation is to be done to get the forceps back than it will cost minimum of 0.5 Mn INR. Shine Keeping the workplace clean “SEE IT CLEAN IT…” For this step let us take an example of a restaurant. If we don’t keep our workplace clean, customers will question the Hygiene of the restaurant and never come back again. In office, Standardize A checklist is to be prepared to keep the first 3S from falling back “WHERE IS THE STANDARD…” Think of Aeroplanes, if we have not implemented 5S in Aeroplanes, not defined minimum fule requirement, it will be stuck in middle of air without any fuel. If there are no standards on how first 3 s will be done in an Aeroplace. There will be so much dissatisfaction in customers, and everyday you might get news about accidents/incidents of Planes in Newspaper Sustain Create a 5S culture by cross functional audits of that area, so that first 4 s does not fall back “ CREATE A 5S CULTURE” Overall I would say that 5S does benefit if implemented outside the manufacturing industry. Cost implications can also be calculated as shown by various examples.
  15. Innovation requires creative thinking; it also requires some data collection on which you make your decision. Lean Six Sigma is a process of finding solution/ideas based on detailed data analysis. Lean Six Sigma never stops innovation/creative thinking. Innovation is more of skill based process and Lean Six Sigma is Knowledge based process. When we have people with good skills in a Lean six sigma project we will come up with an innovative idea. It all depends on team members and the facilitator/team leader. Several Six Sigma tools including the Cause and Effect diagram and the Failure Mode and Effects Analysis (FMEA) promote innovative thinking and team brainstorming. An efficient facilitator paired with a varied and creative team makes the ideal setting for new thoughts to materialize when searching for possible root causes or when determining probable solutions. If we involve Six Sigma methodology in innovation, chances of getting success increases. At the end I would like to Quote “FAILING TO PLAN IS PLANNING TO FAIL”