Machine Downtime Tracking Software

Get to zero unplanned equipment downtime using causal loss.

Tired of interruptions and limited capacity? Track and prevent machine downtime hampering worker productivity.

When downtime tracking is a mix of manual processes and sensor-based data recording, operational teams can’t easily spot and correct the underlying cause of unplanned equipment downtime. Monitoring production downtime accurately at a granular level requires automated, machine-level data. With better data and proactive interventions, it’s easier to solve the real root cause of equipment downtime – boosting capacity and improving lead times.

Reduce unplanned downtime without hours of root cause analysis.

Automated PLC data – no bolt-on sensors required
Automatic fault insights without DIY reporting
Operational excellence built in and on-call

Fully guided process

Audit data, methodology and line balancing software, all in one

Not just production line balancing software, our team provides a guaranteed manufacturing line balance step-change. We’ll guide you through a data-informed audit, implement five levels of control and train your team to use LineView’s line balancing software – all for long-term results.

Built-in benchmarking

Line balance scores make benchmarking easy

Making production line balancing easy is the key to lasting results. Easy-to-understand production line balance scores for every product type with built-in baseline comparisons are built-in within LineView’s line balancing software. Teams can benchmark live data vs. historical- so you’ll never lose your capacity gains.

Additional performance gains

Optional controls to automate restarts and recover speed

Optional manufacturing line balance control unlocks additional performance gains between 2-5%. This supervisory line control module sets optimal restart times on core machines (filler, labeler, packer) to accelerate recovery after downtime.

Tracking downtime is good. Automatically detecting True Causal Loss is better.

Improved equipment downtime tracking is only the first step to better OEE downtime monitoring and management. LineView’s intelligent True Casual Loss algorithm automatically correlates a machine-level fault to the impact on that machine and yourOverall Equipment Efficiency (OEE) score. Further categorising downtime into the six losses of OEE provides an accurate picture of downtime and prioritised actions. By shifting focus from machine downtimes to Causal Loss, continuous improvement teams and operators can move away from reactive interventions that are disruptive and inefficient.

How Downtime Tracking Works:

1. Use LineView’s software to track equipment downtime accurately
Upgrading to automated machine-level downtime tracking and auto-fault detection not only improves production monitoring but also empowers operators and managers with accurate, actionable information – not best guesses.

2. Auto-detect true causes of downtime for more efficient fixes
Armed with the underlying cause of downtime allows teams to fix the constraint on the line instead of the symptoms upstream or downstream.Teams Will save wasted time and labour, benefitting your profitability bottom-line.

3. Optimize management time and worker productivity
Using LineView’s automated casual machine downtime tracking function frees management time to focus on coaching and process improvements. Empowering managers with machine fault-level root causes saves hours of analysis and historical reporting.

4. Speed up changeovers and streamline maintenance planning

Once your team has attacked the largest sources of chronic and intermittent downtime, apply LineView data and tools to changeovers, planned maintenance activities, and other focused improvements.

Sustainability challenges and resource optimization

Sustainability goes beyond greenwashing; global governmental bodies are enforcing stricter environmental laws and reporting.

Moreover, the availability of raw materials such as ground water is reducing each day. 1 out of 3 manufacturing plants are in water scarce regions. LineView understands your commitment towards net zero carbon emissions and reducing water & energy wastage. By optimizing plant processes, LineView minimizes resource use and emissions while enhancing productivity.

Digital Transformation made easy

We recognize that not everyone is tech-savvy. That’s why LineView is user-friendly and intuitive. Our expert team collaborates with you, allowing you to focus on your work while improving results. Unlike traditional MES or SCADA systems, LineView offers fast and easy ROI. Out-of-the-box insights empower team leaders to focus on actions rather than time-consuming DIY reporting. Plus, teams can immediately see the impact of their actions, leading to faster order-to-delivery times.

Zero downtime and 10% OEE improvement are easier with causal loss.

Instead of focusing on individual downtime events, LineView helps you move beyond the symptoms to the true cause of downtime.

Improved OEE, downtime monitoring of microstops, auto fault analysis and productivity tools are the tools your team need for sustainable downtime reduction. And as a bonus? Get a guaranteed 10% efficiency improvement.

Be proactive to prevent machine downtime

Minimum 10% OEE gains

Go beyond symptoms to true causes of downtime

Faster changeovers

Get accurate unplanned equipment downtime statistics

Reduce (or eliminate) costly microstops

Customer stories

Case Study

Coca-Cola Enterprises selects Lineview™ as their system of choice.

Over a three-year period, LineView™ has been implemented on every production line in Europe to help increase efficiency and reduce manufacturing costs.

Case Study

AB InBev China achieves Goals through Data, focus and action.

The world’s largest brewer, AB InBev, recommended LineView™ to their Chinese bottling plant based in Wuhan to remedy the company’s struggles with efficiencies.

Case Study

Chivas Brothers Pernod Ricard increases mechanical efficiency by 17% in six months.

Line 33’s Mechanical Efficiency increased from 60% to 70% after six months of data-driven interventions and focused improvements.