Downtime is an Inevitable Aspect, but Unplanned Downtime Can Be Prevented. Downtime and production losses are something every manufacturer experiences. The good news is technology solutions like MERLIN are available that dramatically reduce the main sources of revenue loss: Unplanned Downtime, Minor Stoppages, and Changeover Time.

When solutions like MERLIN are implemented, manufacturers quickly realize how much time and revenue is lost with traditional strategies that are manual, time-consuming, and ineffective.

Based on more than 25 years of experience in manufacturing, we’ve outlined the top 3 profit killers in the industry and how they can be avoided.

1. Minor Stoppages
   Minor stoppages are typically the most hidden factors of profit loss, with dramatically more impact on downtime and revenue than manufacturers realize.

Traditional manual, paper-based systems rarely capture minor stoppages, and the data is often unreliable.

MERLIN, along with its IIOT technology solutions, captures every downtime event and the root cause of each stoppage.

Example: A packaging manufacturer manually tracked stoppages but only captured unplanned downtime lasting 5 minutes or more.

The manufacturer implemented MERLIN’s Tempus Enterprise Edition platform to gain real-time visibility into machine-level performance, including all stoppages.

MERLIN identified micro stops in just one week, totalling 7 hours. These were unplanned stops that were previously not recorded. The platform also alerted operators at the time of each stoppage so problems could be fixed as they happened.

1. Unplanned Downtime
   Downtime is the largest source of lost production time and revenue. Yet, it’s estimated that 80% of manufacturers cannot accurately calculate their downtime or understand the costs associated with lost production.

MERLIN Tempus provides real-time insight into the source of unplanned downtime, including which machines have the most occurring faults and the most aggregated downtime.

1. Changeover Time
   Changeover time accounts for the largest source of overall downtime. Yet, most manufacturers have little insight into how long changeovers take or what they can do to reduce changeover time.

A SMED initiative (Single Minute Exchange of Dies) is the standard technique for analyzing and reducing the time it takes to complete equipment changeovers. Most SMED initiatives are manual projects using Excel spreadsheets and stopwatches.

MERLIN Tempus accurately compares estimated changeovers vs actual and accelerates cost savings.

Are you ready to stop the profit killers in your manufacturing organization? It’s easier than you think. Rapid implementation of MERLIN Tempus means you’ll have visibility into your plant, line, and machine data in just days! Contact an expert from Memex today to learn more.

Companies involved in a proof-of-concept (POC) project or phased adoption approach typically begin by connecting a single system to the network and enrolling it into a manufacturing operations management system. The success of such a project relies heavily on following the right steps for deploying and commissioning the machine, along with establishing a clear framework of objectives.

Regarding large-scale information systems, network topology plays a crucial role. It encompasses layers 0, 1, and 2, determining the system’s performance, security measures, error detection capabilities, and resource utilization. To ensure an effective topology, it is important to assess and create it carefully, considering factors like performance, security, maintenance, scalability, and management.

Choosing the right machine asset(s) for a POC or phased plan requires clearly understanding the desired outcomes. The objectives may include automatically capturing operational events, and specific process data, enabling operator interaction based on operations, and even auto-creation of jobs, error reason code identification, and operator response lookup. It’s also important to consider machine-specific capabilities, such as multi-spindle functionality, pallets, tombstones, multi-part count, high-speed part count, and its position in the value stream. Is it a finishing machine determining the throughput for a group of operations? Or is it a constraint machine that collects data to assist in resolving constraints and adopting a continuous improvement methodology?

Selecting the appropriate information system for manufacturing operations involves evaluating various options. From legacy systems like SCADA and process mapping to MES, batch-run systems, and emerging operations and monitoring systems, stakeholders must prioritize their desired functions and features. The challenge lies in identifying deliverables and quantifying unexpected aspects, especially with numerous products making similar claims. Factors to consider include the system’s services, distribution capabilities, scalability, expandability, productization, breadth of intellectual property (IP) across manufacturing, IT, system integration, engineering, vendor stability, and longevity.

An essential aspect of successful adoption is the collection methodology. A system that preprocesses events by normalizing and storing them as events into a single source type proves highly efficient, reducing the need for extensive post-processing. On the other hand, systems that collect raw data events as states often face efficiency and performance issues due to analytics and metrics calculations being performed after collection.

The chosen data storage methodology determines the flexibility of the information system. Storing events as sourcing pattern events enables answering both the “what happened” and “why” questions, tracking jobs through operations, recording multiple events over time, and benefiting from an event sourcing patterns approach. Additionally, calculating metrics globally rather than individually for each object in the system reduces complexity and ensures congruent results.

Job management is a critical feature that should be supported by the system, allowing for sales orders, work orders, part numbers, product standards, and operation steps processes. These elements provide granular job-specific information, metrics, and operational states. A structured product management feature should be considered for effective job tracking.

Adaptability is another crucial aspect of a manufacturing information system, enabling the expansion of event categorization and the addition of operational and process states as needed. This flexibility is essential for continuous improvement efforts and tracking new constraint sources or non-conformity reasons.

Once the topology is established, machines are selected, and the information system is chosen, it’s time to plan and execute the roadmap for the POC or phased plan. The roadmap should consist of specific, measurable, and qualifiable objectives that can be successfully applied to the rest of the plant. Internal champions should be selected to allocate necessary production, engineering, and IT resources. Finally, a kickoff meeting with the vendor should be arranged to assess their action plan and determine the distribution of responsibilities.