11 Oct
2017

9 Signs It's Time To Review Your Data Collection Methods

Would you like to know what are the top 9 signs it’s time to review your data collection methods? This blog post might interest you, head this way!

Machine Monitoring
9 Signs It's Time To Review Your Data Collection Methods

Having access to up-to-date data is critical to the productivity and efficiency of a manufacturing company. Data collection methods not only ensure a level of quality, but also contribute to the reaction time in case an issue arises.

Here are the 9 signs you must review your data collection methods: 

1. Human errors creep into your data

Using paper or spreadsheets to collect data can be useful and represent very minimal costs to implement. While it might, in some cases, be sufficient for a small factory, it is hard to scale and very costly in terms of direct man hours. It represents a lot of manual entry and there is an exponential potential for this data to be wrong or misinterpreted.

Every time there is a human interaction with the data, there is a chance for a human mistake to creep in. Whether it is when the data is first collected, transcribed from paper to excel, or when it is compiled to be interpreted, a misplaced comma or an unperceived typo might make a difference in the results and impact the actions we take following the interpretation of this data.

It might be time to let your equipment data to be collected by a system that eliminates human errors. Discover a real-time data collection software that can help.

2. You get data at the end of the week, it's already to late

What would be the advantage of having accessible data that is no longer relevant? By the time the data is collected, compiled and shared it’s already too late to take action.

As discussed in a previous article, 5 Things Top Manufacturing Companies Do to Save Time, leading manufacturing companies rely on real-time data collection and analysis to increase and maintain efficiency and productivity levels. If your data collection boils down to reports submitted at the end of the week, it may be time to change your data collection methods. Being able to access data in real time, which allows you to act quickly, means you don’t waste time and resources.

3. You have the "Everything needs to be measured" syndrom

As explained in another one of our blog posts, Smart Manufacturing: When & What to Connect in your Factory, it is important to set clear goals based on your business needs. By doing so, you can pinpoint exactly what kind of data you need to collect and consult. By automating your data collection and visualization, you can filter results for relevance and solve real business problems.

4. You are drowning in data

Having a ton of data can be overwhelming. Collecting customer data from transactions or surveys can be useful, but when you have too much of it, data just piles[CL1] up. Being able to filter for relevant data can lead to actually analyzing data that is compiled rather than sifting through irrelevant findings or worse, not even getting to important information.

5. Your systems don't speak to one another (PLC, ERP, equipment)

Different systems and machines yield data in different formats from different sources (PLC, ERP, Equipment). Calculating and translating this data across multiple platforms was once a task reserved for people. This meant a lot of mental math, or even written calculations, either way, it took too much time. Once data collection is automated and the collection process is updated, this information can be automatically translated via the software in your Smart Factory setting.

6. You have access to your data only within your factory walls

Sometimes you aren’t on the factory floor to witness events as they happen. That’s where mobile visualization becomes a game changer, giving you access to the data of your Smart Factory directly on your smart phone.

Executives & consultants are not always at your location and they often need quick access to the data to make relevant business decisions. Not having to send a ton of emails with Excel attachments is definitely a time saver.

7. Your data doesn't speak for itself

Data collection can compile a lot of useful information, but it can be overwhelming. Having too much data to look at might mean overlooking key information. It is, of course, possible to sort things out, but by automating your factory’s data collection methods, your data will be presented clearly and in a way, that is visually appealing, easy to understand and solution oriented.

8. Your data is not precise enough

The quality of data collection in an environment that relies on it for productivity and efficiency is critical so that manufacturers can spot problematic areas and come up with solutions. You can’t do that if your data is unreliable or badly collected. Not being able to resolve a problem because of inaccurate or inadequate reports is costly, both in terms of time and resources, and interferes with production.

9. It takes too long to react when there's unplanned events

When something unplanned happens on your production line or on one of your equipment (such as unplanned downtime), it takes a while for the information to be communicated to the right person. This situation can create delays that might impact your client.

Nowadays you can automate the communication when critical standards that aren't met with instant notifications on the employees email or smartphone. It allows your team to save some precious time and your plant to run efficiently.

If you can relate to this experience, it might be the right time to start talking about automating your data collection methods. 

 

Want to learn more?
Download the ebook
Related blog articles

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
25
Jul 2023

Breaking Down OEE for Shop Floor Success

Discover how breaking down Overall Equipment Effectiveness (OEE) into relevant metrics for the shop floor drives operational success.

English
21
Jul 2023

CDAP: $15,000 Grant To Jump Start Canadian Manufacturing Digital Transformation Projects

With the rise of digitalization in the manufacturing industry, the Canada Digital Adoption Program (CDAP) and Worximity's smart factory performance manager software suite are helping manufacturers increase throughput and reduce production costs.

English
27
Jun 2023

Au-delà des chiffres : maximiser le retour sur investissement dans le secteur manufacturier grâce à l'analyse de données

L'intelligence des données provient de chiffres bruts. Ces informations doivent être analysées et traduites en actions ayant un impact sur l'entreprise. Mais avec des données qui s'accumulent plus vite qu'elles ne peuvent être transformées en analyses de données manufacturières, les entreprises ratent des opportunités.

French

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
23
May 2024

Exemples de Lean Manufacturing provenant des principaux leaders de l’industrie

La mise en œuvre du Lean Manufacturing peut vous apparaître comme un défi colossal. En regardant ce que les meilleurs ont accompli en appliquant les principes du Lean Manufacturing, vous serez à la fois inspirés et motivés.

French
25
Apr 2024

How to Analyze Throughput Rate

Throughput rates are an important measure of factory performance. Not only does throughput indicate whether the factory can meet customer demand, but it's also an indicator of overall plant efficiency.

English
15
Apr 2024

Les meilleurs outils d’amélioration continue pour les entreprises manufacturières œuvrant dans le secteur agroalimentaire

Dans le paysage concurrentiel du secteur agroalimentaire, la mise en œuvre de méthodologies d'amélioration continue n'est pas seulement un choix : c'est une nécessité pour rester compétitif.

French