Customer Stories
Model AG

How Model AG Can Reduce Laboratory Staff Workload by Half with 1LIMS

Model AG enlisted the expertise of 1LIMS to digitalize its quality control processes. After examining their workflows, we pinpointed opportunities to save costs and enhance efficiency. Transitioning to digital processes with 1LIMS could yield annual savings of up to CHF 41,067, cutting the workload for laboratory employees managing quality data by 50%.
Model AG develops, produces, and supplies high-quality display and packaging solutions made of solid and corrugated cardboard. The company was founded in 1882. Today, it employs around 4,600 people at 15 European locations. All Model AG's factories hold ISO 9001 quality management certification.
Website
Headquarters
Weinfelden, Switzerland
Industry
Packaging
Key value delivered
Identified inefficiencies in existing quality assurance processes
Evaluated potential financial benefits of transitioning to digital workflows
Outlined an action plan for deploying a customized LIMS to digitize laboratory operations
Dashboard mockup

Project Overview

Model AG was looking to modernize their quality management processes. This involved replacing the outdated Microsoft Access database currently used in the laboratory with a cutting-edge Laboratory Information Management System (LIMS). But before committing to this transformation, they sought an external perspective to define the roadmap for the digitalization project based on their existing circumstances. They engaged 1LIMS to provide guidance.

Our team conducted a comprehensive process analysis at Model's facility in Weinfelden, Switzerland, to assess their quality management processes, identify opportunities, and offer a customized solution to existing challenges.

Our analysis revealed that digitalizing laboratory processes could reduce the laboratory workload by 50%, saving approximately CHF 41,067 annually. The initial investment in the 1LIMS solution could be recovered through increased efficiency and the ability to allocate saved time to valuable activities.

Read on to learn more about the LabCheck workshop we've organized for Model AG and what our assessment has shown.

Digitalization goals

Model AG's initiative to drive change in quality management

With 4,600 employees across 15 European locations, Model AG is one of Switzerland's top producers of paper and corrugated cardboard for packaging. Since 1882, Model AG has continually evolved, embracing modern technology to automate its production processes.

With a commitment to enhance product quality, Model AG undertook a strategic initiative to implement a recognized product safety system by 2030. As part of this initiative, they aim to allocate resources toward skilled personnel and modern technology to improve complaint rates, lead times, and deliveries, ultimately enhancing productivity.
They decided to upgrade their quality management processes in line with this vision.
Dashboard mockup

The challenge

Data siloes and operational struggles

Currently, Model AG uses the Microsoft Access database system in the laboratory, which is scheduled for replacement in 2023. The current technology setup, which includes Access and SAP systems alongside manual data handling and storage, results in inconsistencies and inefficiencies in data management.

Data siloes not only complicate the availability and usability of measured values but also make it challenging to trace the origin, history, and destination of a product or component. This traceability is crucial to ensure products meet quality standards and can be recalled easily.
Model AG sought 1LIMS's digital consulting service to enhance overall quality across its operations. They aimed to:
Streamline laboratory processes
Improve data accessibility
Ensure comprehensive documentation and traceability
We provided LabCheck, a workshop designed to analyze current processes and devise a digitalization roadmap for quality management.

Solution

LabCheck Workshop Goals

Objective 1
Assess the opportunities, risks, and potential of digitalization within quality control and laboratory operations
Objective 2
Determine the value of implementing a Laboratory Information Management System (LIMS).
Dashboard mockup

LabCheck Workshop

Following the foundational principles of Lean Six Sigma (Define, Measure, Analyze, Improve, and Control), we first needed to analyze the existing process to improve the efficiency of quality management at Model's laboratory. We evaluated the existing process using Gemba Walk, Process quantification, and SIPOC analysis.
Gemba Walk
SIPOC analysis
Process quantification

Quality (Gemba) Walk:

A tour along the entire value chain of paper and corrugated cardboard production

To better understand Model AG's operations and identify inefficiencies and opportunities for improvement, we needed to observe and understand the process of paper and corrugated cardboard production firsthand. We visited Model's facility in Weinfelden, Switzerland, which employs 580 employees.

Accompanied by Model AG's Head of Laboratory, Quality Management specialist, and laboratory employee, we walked through the following production areas to gain insights into the operations of the facility and identify specific areas for improvement:
Dashboard mockup
Dashboard mockup

Process mapping and SIPOC analysis

Following the Quality Walk, we used a SIPOC diagram to outline each process's inputs and outputs. This visual mapping tool helped us see the big picture and agree on necessary changes.

Process quantification

At Model AG, the laboratory operates with a lean team of 2 dedicated employees, supported by a suite of 9 devices, managing the processing of 15,000 items. The lab employees conduct 1,040 sample analyses yearly, covering 416 external orders and scrutinizing an extensive range of 18,460 parameters.
~1040
Samples analyzed per year
~18,460
Measured parameters per year
~416
External orders per year
9
Test equipment in the laboratory
2
Employees in the laboratory
15,000
Items

Key inefficiencies identified

As a result of our evaluation, we identified the following inefficiencies in quality control procedures in the laboratory:
Inefficient order handling
Orders from five different suppliers and finished test protocols are distributed via email, leading to potential inefficiencies in tracking orders.
Manual data handling
Raw data sheets are filled out manually and stored in folders within the laboratory, hindering data traceability. Test reports are filled out by hand, then scanned and sent as PDFs to internal departments, which is error-prone and inefficient.
Data fragmentation
The data from quality checks is stored in multiple formats and locations, including Access database, paper notes, Excel entries, and scanned PDFs on SharePoint. This fragmented approach increases the risk of information loss and makes accessing and managing data difficult.

In numbers

Manual processes and data fragmentation make data management in Model AG's laboratory costly, time-consuming, and labor-intensive. The KPIs we've analyzed demonstrate this.
49 hours
Per week is spent on data management
1 hour
To collect and document data for each sample
116%
data management workload per 1 FTE
CHF 81,667
Costs incurred
per year

Results

The value of implementing 1LIMS in Model AG's laboratory

To enhance laboratory efficiency and cut costs, we've recommended that Model AG implement centralized management of all quality data and activities within 1LIMS. Our solution can offer the following benefits:
Secure 
data management
78
%
Error
minimization
Quick data 
processing
31
%
Increase in sample throughput with the same FTE
Simplified laboratory operations
45
%
Reduction in quality analysis costs

Suggested best practices

As part of our opportunity analysis, we also proposed the following best practices that can be integrated into 1LIMS to address current challenges.
Objective
Best practice
Streamline data
management
Deploy tablets in the laboratory for data collection, analysis, and management
Enable visual recording of products/samples using a photo database
Implement QR codes and labels for automated sample management
Incorporate filter functions for all laboratory data within 1LIMS to speed up data search
Automate the creation of COA reports
Integrate dashboards, control charts, and trend analyses to assess analysis values visually
Improve compliance and data transparency
Achieve complete traceability of data and laboratory activities with a centralized LIMS
Automate the creation of COA Implement change control to track actions that happen in the laboratory for better accountability and compliance
Manage and record in-process controls (IPC) in the LIMS
Enhance operational
efficiency
Ensure a smooth flow of information from other departments to the laboratory using a centralized quality management system
Integrate 1LIMS with existing IT systems like SAP and MES and connect it to laboratory devices and sensors to allow for automated transfer of master data and production orders and real-time visibility of the product status
Introduce risk-based analysis recommendations with dynamic inspection plans to speed up quality management workflows while improving compliance

1LIMS implementation plan

Based on Model's resources, implementing 1LIMS can take three to six months, from customization to launch. Once the solution is implemented, we suggest gradually integrating it into existing IT systems and connecting it with laboratory equipment to automate data transfer and improve traceability.Here is the overview of the main phases of 1LIMS implementation:
Objective 1
Replace raw data sheets, Excel spreadsheets, and the Access database with 1LIMS for centralized quality data management.
Centralize all master data (items, parameters with specifications and methods, test plans)
Configure order and sample entries with relevant information
Incorporate analysis management
Implement graphical evaluations using Quality Control charts
Employ labels and QR codes for laboratory sample management
Objective 2
Integrate 1LIMS with internal software systems for automated data transfer.
Interface with Production System Integration with ERP
Interface with SAP R/3
Interface to MES (possibly with prior cost-benefit analysis)
Expanding the use of labels and QR codes for sampling in production
Risk-based analysis with dynamic test plans
Integration of laboratory equipment

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