PREPARATION OF TIME STUDY (INDUSTRIAL ENGINEERING) WHICH DETERMINES THE PRODUCTIVITY IN MANUFACTURING

SHARING MY PROFESSIONAL EXPERTISE OF WHAT HAD BEEN LEARNT IN THE MANUFACTURING ORGANIZATIONS WHICH PREDICTS & DETERMINES THE PRODUCTION CUM PRODUCTIVITY & WHAT IS THE ROAD MAP FOR "THE PREPARATION OF TIME STUDY" THROUGH INDUSTRIAL ENGINEERING.

Thinking you want to perform a time study? This is a decision that will benefit you and your company immensely moving forward. However, it isn’t a process you can jump into with no practice or preparation. You will need to use precise methods, and if you don’t take the time to learn them, the whole process might be for nothing.

To ensure your time study delivers the most significant results possible, here are seven tips and instructions for prepping for a time study of your own.

1. Develop a Strong Rationale for Conducting the Study

Why do you want to do a time study? The answer might be obvious to you, or it might not. Most time studies are conducted merely to learn how long things take, but there can be other reasons, as well. Maybe you feel performance is lacking and are looking for ways to speed it up. Or perhaps you’re simply looking for a rubric so you can reasonably evaluate your employees’ performances.

Whatever your reasons are for conducting this study, its best to firmly establish them for yourself before you begin. If you’re feeling a little unsure about your motivations, consider putting them down in writing. If any employees express concerns about the study, you will be ready and equipped with a satisfactory answer for them.

2. Choose What You Want to Measure

To keep your study manageable, it might not be realistic to measure every single aspect of work and manufacturing that happens under your roof. Instead, set boundaries and practical limits for your study. Decide how you will handle things like worker breaks. Choose how many variables you want to incorporate into your research.

If you’re not confident of how to handle all the different factors, consider asking your employees questions that might help you. Ask them:

·        Where they think they spend most of the day

·        What part of their work is the most time consuming

·        How long they think it takes

Ask multiple employees these questions, and compare their answers. You might be surprised at the responses you get, and you also might find the inspiration you need to decide which direction to take your project.

3. Decide How Detailed You Want to Be

A time study can be as complicated or as simple as you want it to be. You can express any step in the manufacturing process simply or not, and it’s up to you to decide how to quantify this. Do you want to measure data on each tiny individual sub-set of time, or do you only want to measure the larger blocks as whole units?

Realize the more you choose to break the units of time down, the more complex and challenging your study will be, but the higher its potential for improving your operations grows. On the other hand, a simple study will be much easier, but it may not be quite as helpful or insightful.

4. Designate a Representative Time Period to Study

It’s important that your time study takes place during a period that accurately represents your company’s typical work environment. For example, don’t perform your study while half the employees are on vacation, your floor is being repainted or you’re being evaluated by the higher-ups. Instead, choose a regular period when everything is operating as usual, and your employees are performing at their normal capacity.

The risk of performing your study during an irregular period is that the data you collect will not accurately represent your operation. Thus, any conclusions you arrive at based on this data will be inherently flawed and almost if not entirely useless.

5. Consider Ignoring the First Several Days of Results

In many cases, it may be wise to simply ignore all the results collected from the first few days of your study. This may initially sound incredibly counter-intuitive, but consider it this way. Many of your employees may be nervous and on-edge about being recorded and studied. As a result of these nerves, their performances may be fluctuating wildly far off the mark of their ordinary work. As such, data collected during these days is unlikely to be representative.

After a day or two, your employees will probably shake off the worst of their nervousness and work will mostly return to normal. Once this happens, you can begin recording results.

6. Use Responsible Sampling Procedures

For your data to be accurate and representative, you must follow best practices for collecting work samples. Firstly, you’ll need to be aware of your sample size. Because you’ll need to allow for a margin of error on both ends of your data, you should collect a large enough sample size that this will not matter very much.

Secondly, the samples must be truly random. If you are always taking your samples from the same worker, this data will not be representative of your entire operations. Similarly, if you’re only choosing the best or worst worker, this is not random and will not yield helpful and informative data.

7. Review Your Basic Understanding of Data Trends

If you’re going to complete a statistical study, it’s best to make sure you have a solid understanding of data trends and the primary measures of central dependency. Review such basic terms and concepts as:

Outliers: These are data points that are far higher or far lower than almost every other one you have collected. It is fair to assume that something unusual happening to produce these numbers and that they are not representative of the data as a whole. So as not to skew your calculations, it is often best to eliminate extreme outliers from your data altogether.

Average: Also known as the mean, this number refers to the figure that is the best representative of all the collective data. Add each data point together, then dividing by the total number of points to reach this figure.

Median: This value represents the exact midpoint of all the data points collected. Exactly half your data points will be lower than the median, and half will be higher.

Mode: Representing the most frequently occurring value or data point, the mode can help you determine trends and commonalities within your manufacturing process.

Spread: This refers to the overall shape of the distribution of data points. If the points are all clumped together, it shows little variability and will create a tall, narrow shape. On the other hand, points that are vastly spread-out display an enormous variety of data points and will create a low-lying, spread-out shape.

SUNDARAMURTHY VELMURUGAN – linkedin.com/in/sundaramurthy velmurugan 299586110   LEATHER PROFESSIONAL CONSULTANT from a2z Leather Professional Consultant, PONDICHERRY.

velvbl@gmail.com & velmurugan1959@yahoo.co.in - Whatsapp: +918973231705