12 Apr
2018

Machine Monitoring: How Competitive Factories Decide Better

This post explores how valuable the data is that’s gathered in production via machine monitoring, and how cross-functional teams can collaborate better when the data is shared.

Machine Monitoring
Machine Monitoring: How Competitive Factories Decide Better
Machine Monitoring
Machine Monitoring
Food & Beverages Processing
Text Link
Consumer Product Goods
Text Link
Material Building & Construction
Text Link
Original Equipment Manufacturer (OEM)
Text Link
Pharmaceuticals & Supplements
Text Link
Packaging & Co-manufacturing
Text Link
Text Link

Paper-based data collection systems or no data collection systems are a serious problem for manufacturers who want to cut costs, maximize profitability and stay competitive.

Not knowing what’s going on across the factory floor can result in massive productivity disruptions and waste. With the capabilities and accessibility of sensor-based data collection systems, there are fewer barriers to implementing an automated data collection system and real-time dashboard display.

Decreasing downtime with machine monitoring

Even providing basic information such as downtime on real-time dashboards and mobile devices can have a huge impact on uptime. Everyone will react faster to seeing red, and make more of an effort to fix the problem and get back into a green zone. As more data is captured, trends can assist in preventing downtime in the future.

Worximity_Lean_Manufacturing_Waste_Waiting

Improving quality with machine learning

By tracking which cells or lines are consistently above and below acceptable quality levels, you can quickly identify and remedy underperforming operations. Continuous monitoring throughout the process helps identify quality problems early for more effective, less costly solutions that don’t rely on manual quality checks.

With enough data and the proper analytics, machine learning can start to predict quality issues. For example, if a situation has occurred several times in the past when the temperature is at a certain level, a certain raw material is at the upper tolerance limit, and a quality issue arises in a much later step in the process, machine learning can flag that pattern when it’s happening. Identifying a problem before it even occurs is a revolutionary approach to controlling quality. Pattern identification is a powerful potential benefit of an IoT solution and making the most of all the data you’re collecting.

Scheduling with better precision

Gathering actual production data, with machine monitoring, gives you more precise, real-world data to work with when planning and scheduling. Sensor-based data enforces consistency, eliminating variances caused by different operators reporting information using personal interpretations.

If there’s a suspicious variance in time required to produce the same item, analytics can highlight that discrepancy, and link to related data so the causes of below-average performance can be investigated and remedied.

Improving inventory accuracy

Machine-generated counts of finished goods produced are much less prone to inaccuracies and errors than manual systems. With real-time information there is no waiting for a manual count. The actual levels of all inventory are available at all times and in all stages of the production cycle.

With true inventory counts, capabilities can be determined with much higher confidence, allowing order fulfillment rates to increase.

Planning maintenance with machine monitoring

If a something on a machine needs repair, do you stop the line to fix it or keep patching the process together to keep the line moving? That’s a strategic decision that shouldn’t necessarily be made by the machine operator. With real-time dashboard information, the maintenance issue can be made visible to the level of management required to decide when to schedule the required fix.

Real-time data displays offer many benefits that show results quickly.

Discover more benefits of real-time dashboards.

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.
11
Apr 2024

Votre guide en matière de contrôle statistique du processus (CSP)

En tant qu’entreprise manufacturière, il est essentiel de comprendre le contrôle statistique du processus pour survivre et prospérer dans l’environnement hyper-compétitif d’aujourd’hui.

French
10
Apr 2024

Définir la différence entre le temps de production et le temps de cycle

Le temps de cycle et le temps de production sont des indicateurs clés de la performance manufacturière. Découvrez ce que chacun signifie et comment les utiliser pour augmenter la productivité dans le cadre de votre processus de production.

French
13
Mar 2024

Moteurs d’efficacité manufacturière : Monitoring des machines et du TRG

Le monitoring des machines et du TRG (taux de rendement global) sont efficaces pour améliorer l'efficacité globale, mais quelle est la différence entre eux et qu'est-ce qui est le mieux adapté à vos opérations?

French
13
Mar 2024

Engines of Manufacturing Efficiency: Machine Monitoring and OEE

Machine Monitoring and OEE (Overall Equipment Effectiveness) are effective at boosting overall efficiency, but what is the difference between them and what is best for your operations?

English