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WorkClout Case Study: Flexible Packaging
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Aug 8, 2019

Overview

Flexible packaging is one of the biggest manufacturing industries in the US, with over 30 billion in annual sales and growing, the industry is projected to 3x within a span of 5 years. Unlike most manufacturing industries, flexible packaging has always been driven by advancements in industry-specific machine technology. These advancements in packaging capabilities bear the need to provide more customized product specifications to customers. Things such as intelligent sensor films, film barriers, authentication seals, RFID technology and much more have increased the complexity in job processes causing an increase in compromised promise dates. 

Many industry leaders in flexible packaging have now found success in the adoption of advanced production scheduling software and manufacturing execution software to aid in the increased demand for customization and process.

Case Study

The case study below highlights one of the many flexible packaging manufacturers that utilize WorkClout as their primary tool to plan, execute and measure their production process. This study contains data recorded over a period of 2 months before implementation and 2 months after the adoption and implementation of WorkClout.

WorkClout is a top-rated advanced production scheduler (APS) and manufacturing execution software (MES).

Read more here: Capterra

Company A*

Company A is a mid-sized flexible packaging company 

  • Established in 2013 
  • Serves over 1000 clients 
  • 50-70 employees

Background

Before using WorkClout, Company A’s production process was managed via paper and excel. This results in a severe lack of insight into the overall quality rate during production, leading to an increased number of job rework that was required to meet customer standards. Below are the reasons why the quality rate was a relevant issue.

  • Paper and handwritten job specifications which caused communication delays, rushed orders and inaccurate runs.
  • Zero accountability of set up times, run times and run counts, overall lack of insight of where the bottlenecks where located. Times were logged via paper and stored in binders.
  • Lack of job prioritization causing frequent changes to the schedule, which resulted in a loss of time.

A sample size of 66 jobs was followed and analyzed over a period of 1 month before implementation to establish a baseline metric of current production state. There were three specific metrics that we looked at.

  1. Job Ticket Delays - We asked for operators to note each time a run required clarification and log the average delay times over the course of each run over the 2 month period.
  2. Run Times and Defects - We collected the average run times and defect counts per each run associated with the jobs and analyzed them on an excel sheet. Our assumption is that the actual run duration minus the est. run durations are to account for defects.
  3. Est. vs Actual Lead Time - We recorded the est. vs actual lead time for each job to see which order promise dates were compromised.

Looking at the data from a holistic perspective you can easily infer that these metrics were really hurting the productivity of Company A’s production process as a whole.

  • Around 24.25 production hours were lost over a period of a month due to paper job tickets.
  • Around 316.8 additional production hours were allocated to runs w/ defects.
  • This resulted in an average increase in the original order lead time of 3 days.

The delays equate to a compounding average loss of $81,852 annually, assuming average hourly labor costs and total average jobs completed annually.

Hypothesis

By leveraging WorkClout’s visual job management, production schedule, and operator portal. Company A’s employees would be able to streamline each job’s production process into one platform, enabling all employees the ability to instantly view job progression and next steps.

  • Digitized job specifications would allow for instant communication to machine operators, decreasing overall lead times by multiple days my minimizing delays.
  • Tracking time, quantity produced and defects for every machine and run would allow for increased visibility into bottlenecks over time, increasing overall equipment efficiency. Enabling production managers that ability to further identify bottlenecks in the process.
  • Visualization and prioritization of runs on the production based on order promise dates would allow for better job management and more accurate lead times.

Using WorkClout

After observing and documenting these metrics over a period of 1 month. We began tracking the same metrics after implementation with WorkClout and below are the results.

A sample size of 57 jobs was followed and analyzed over a period of 1 month after implementation to compare results after using WorkClout for a period of time. There were three specific metrics that we looked at.

  1. Job Ticket Delays - We asked for operators to note each time a run required clarification and log the average delay times over the course of each run over the 1 month period. These logs were tracked on WorkClout via pauses using the operator portal.
  2. Run Times and Defects - We compared expected run durations vs actual run durations of jobs over the period of time. All the data was logged via the operator portal and report generated via WorkClout.
  3. Est. vs Actual Lead Time - We compared est. lead times and actual lead times over the period of time. All data was logged and a report generated via WorkClout.

After implementing and having used WorkClout you can see that almost all categories in which delays occurred saw an immediate improvement.

  • Less than 1 hour of time spent on job clarification after going digital and getting information via the operator portal.
  • Over 290+ hours were saved over a span of a month by capturing and digitizing all operating data through an operator portal, accountability was enforced and run times reduced. 
  • Lead times were drastically improved, Company A is now delivering on average 4 days ahead of schedule by gaining visibility into production using the production schedule.

Summary

Company A has been able to reduce its average lead time by over 5 days by using WorkClout to streamline communication, plan production, and execute with precision.

By reducing the number of delays throughout production, Company A has increased profit margin by over $76,464 annually.

Documented and Written by the WorkClout data team in 2019. Company A

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