The Challenge
Mitchel Lincoln, a family-owned leader in sustainable packaging and corrugated manufacturing since 1965, faced a critical capacity optimization challenge that threatened to limit their growth potential. As the number one market shareholder in Quebec’s corrugated packaging industry, the company operates five manufacturing facilities with a combined 950,000 square feet of production capability. However, their Drummondville plant presented a unique operational puzzle that required sophisticated analytical capabilities.
The Capacity Planning Manufacturing Dilemma
In 2025, Mitchel Lincoln’s Drummondville facility produced 1.4 billion square feet of corrugated packaging products, operating at what appeared to be maximum capacity. The company had recently invested in a new corrugator machine with theoretical capacity of 2 billion square feet annually, representing a significant 43% increase in potential output. However, despite this substantial equipment upgrade, actual plant throughput remained constrained at the previous 1.4 billion square feet level.
The corrugated manufacturing process at Mitchel Lincoln involves intricate material flow patterns that begin with the corrugator machine creating corrugated sheets, followed by complex routing through transformation presses, packaging operations, and shipping departments. The facility operates with sophisticated material handling systems including an automated train that transports corrugated sheet piles throughout the plant, a 65-lane garage storage system, and multiple conversion presses that transform raw corrugated sheets into finished packaging products.
Critical Operational Constraints:
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Suspected bottlenecks in train movement, press operations, or packaging lines
- Complex product mix with no standard products - every customer order requires custom manufacturing
- Material handling challenges between corrugation and conversion operations
- Limited visibility into actual constraint locations and optimization opportunities
- Need for data-driven investment prioritization to achieve 2 billion square feet capacity
The challenge extended beyond simple capacity analysis to encompass the fundamental question of how are cardboard boxes manufactured at scale when dealing with unlimited product variety. Mitchel Lincoln’s corrugated cardboard manufacturing operations serve customers across diverse industries, each requiring unique box specifications, printing patterns, cutting configurations, and finishing requirements. This complexity made traditional capacity planning methods inadequate for identifying the true constraints limiting plant performance.
The Need for Advanced Simulation Analysis
Mitchel Lincoln’s leadership recognized that achieving the 2 billion square feet target would require sophisticated analysis capabilities that could model the complex interdependencies within their corrugated manufacturing operations. The company needed to understand where bottlenecks actually occurred, quantify the impact of various improvement scenarios, and develop a data-driven roadmap for capacity optimization investments.
The corrugated packaging industry’s demand for customization creates unique analytical challenges. Unlike manufacturing environments with standard products and predictable routing patterns, Mitchel Lincoln’s operations must accommodate virtually unlimited product variations while maintaining efficient flow through shared equipment resources. This operational complexity demanded simulation technology capable of modeling custom routing patterns, variable processing times, and dynamic resource allocation decisions.
Traditional capacity analysis methods proved insufficient for addressing these challenges. Spreadsheet-based approaches could not capture the dynamic interactions between the corrugator machine output, train movement logistics, press utilization patterns, and packaging line coordination. The company required a solution that could model these complex relationships while providing actionable insights for optimization investments.
The Solution
Mitchel Lincoln partnered with SimWell, a leading simulation consulting firm, to develop a sophisticated Simio-based model that could accurately represent their corrugated manufacturing operations and identify optimization opportunities. The collaboration leveraged Simio’s discrete event simulation capabilities to create a detailed digital representation of the entire Drummondville plant, from corrugator machine output through final product shipping.
Advanced Corrugated Manufacturing Simulation Approach
The simulation modeling approach recognized that corrugated packaging production involves complex material flow patterns that traditional analytical methods cannot adequately represent. SimWell’s team developed a full-plant Simio model that captured the intricate relationships between corrugation, material handling, conversion, and packaging operations while accommodating the unlimited product variety characteristic of the corrugated cardboard manufacturing industry.
The modeling framework utilized Simio’s object-oriented architecture to create modular, reusable components representing key plant assets. The corrugator machine, train system, garage storage, transformation presses, and packaging equipment were all developed as configurable Simio objects that could be easily modified to test different operational scenarios and equipment configurations.
Technical Implementation Architecture:
The simulation model structure followed input-process-output methodology where inputs included historical production data, order characteristics simplified into product families, equipment parameters, cycle times, setup requirements, and workforce availability schedules. The process section contained detailed material flow logic, routing rules, operational constraints, and equipment-specific processing requirements. Output metrics focused on throughput analysis, equipment utilization tracking, bottleneck identification, and work-in-progress queue analysis.
The model began simulation at the corrugator machine exit point, where corrugated sheet piles are created and enter the plant’s material handling system. The train system, operating along dedicated lanes throughout the facility, transports piles from the corrugator to various transformation presses or to the 65-lane garage storage system when presses are occupied. Some oversized piles require floor storage due to garage capacity limitations, adding complexity to the material handling optimization challenge.
Comprehensive Plant Layout Modeling
The Simio model accurately represented Mitchel Lincoln’s physical plant layout, including the corrugator machine location, train movement paths, garage storage configuration, transformation press positions, laminator operations for specialty printing requirements, and packaging line arrangements. This detailed spatial representation enabled analysis of material flow efficiency and identification of potential layout optimization opportunities.
The garage storage system modeling proved particularly critical, as the 65-lane configuration creates complex decisions about pile placement and retrieval sequencing. The simulation captured how train movement efficiency depends on garage utilization patterns and pile accessibility, revealing optimization opportunities that would be impossible to identify through traditional analysis methods.
Transformation presses were modeled with realistic processing times, setup requirements, and capacity constraints. The model incorporated the reality that all orders require custom setup configurations for specific customer requirements, including printing patterns, cutting specifications, and finishing operations. This customization requirement creates complex scheduling challenges that the simulation accurately represented.
Advanced Scenario Analysis Capabilities
SimWell utilized Simio’s experimentation capabilities to conduct systematic analysis of various improvement scenarios. The modeling approach enabled rapid parameter adjustments and response variable tracking, facilitating sensitivity analysis to identify the most impactful optimization opportunities. The team tested multiple scenarios including automation improvements, continuous improvement initiatives, and capital investment options.
Scenario Categories Analyzed:
Automation Scenarios focused on enhancing train movement efficiency and decision logic optimization. These scenarios explored how intelligent routing algorithms could improve material handling performance and reduce bottleneck constraints.
Continuous Improvement Scenarios evaluated realistic operational enhancements using lean manufacturing principles, setup time reduction, and downtime minimization strategies. These scenarios provided insights into achievable improvements through operational excellence initiatives.
Investment Scenarios analyzed the impact of new equipment additions and existing equipment capability enhancements. These scenarios quantified the capacity gains achievable through various capital investment options, enabling data-driven investment prioritization.
The experimentation framework enabled comprehensive testing of scenario combinations, allowing Mitchel Lincoln to understand how different improvement initiatives would interact and complement each other in achieving the 2 billion square feet capacity target.
Data-Driven Bottleneck Analysis in Corrugated Plants
The simulation model provided unprecedented visibility into actual constraint locations within Mitchel Lincoln’s corrugated manufacturing operations. Through detailed bottleneck analysis in corrugated plants, SimWell identified that the train system represented the primary constraint limiting plant throughput, followed by secondary bottlenecks at the transformation presses.
The analysis revealed that train movement efficiency significantly impacted overall plant performance, as material handling delays cascaded throughout the production system. The model quantified how train utilization patterns affected garage storage efficiency, press feeding schedules, and overall material flow optimization.
Press utilization analysis identified specific equipment pieces operating at capacity limits and revealed opportunities for load balancing across the press network. The simulation demonstrated how press scheduling optimization could improve overall system throughput while maintaining the flexibility required for custom product manufacturing.
The Results
The Simio-based simulation analysis delivered critical insights that fundamentally transformed Mitchel Lincoln’s approach to capacity optimization and investment planning. The comprehensive modeling effort provided definitive answers about constraint locations, quantified improvement opportunities, and established a clear roadmap for achieving the 2 billion square feet capacity target.
Definitive Bottleneck Identification
The simulation analysis conclusively identified the train system as the primary constraint limiting Mitchel Lincoln’s corrugated manufacturing capacity. Despite the corrugator machine’s 2 billion square feet theoretical capacity, material handling limitations prevented the plant from achieving throughput levels beyond the existing 1.4 billion square feet. This finding redirected the company’s optimization focus from production equipment to material handling efficiency.
The bottleneck analysis in corrugated plants revealed that train movement decision logic represented a critical optimization opportunity. The existing train routing algorithms did not optimize for overall system efficiency, creating unnecessary delays and reducing material handling capacity. The simulation quantified how improved train dispatch logic could significantly enhance plant throughput without requiring additional capital investment.
Secondary Constraint Analysis:
Following train optimization scenarios, the simulation identified transformation presses as the next limiting factor in plant capacity. The analysis revealed that press utilization patterns created secondary bottlenecks that would emerge once train efficiency improvements were implemented. This insight enabled Mitchel Lincoln to develop a phased optimization approach addressing constraints in priority order.
The press bottleneck analysis demonstrated how setup time reduction and scheduling optimization could enhance capacity utilization. The simulation showed that even modest improvements in press efficiency could yield significant throughput gains when combined with train optimization initiatives.
Quantified Improvement Scenarios
The simulation testing revealed specific performance improvements achievable through different optimization approaches. Automation scenarios focusing on train movement optimization showed measurable throughput gains, though not sufficient alone to reach the 2 billion square feet target. The analysis demonstrated that intelligent train dispatch algorithms could improve material handling efficiency while reducing work-in-progress accumulation.
Continuous improvement scenarios testing realistic operational enhancements through lean manufacturing principles showed additional capacity gains beyond automation improvements. These scenarios validated that combining multiple improvement approaches would be necessary to achieve the full capacity target.
Investment Scenario Results:
Capital investment scenarios provided quantified analysis of equipment additions and capability enhancements required to reach 2 billion square feet capacity. The simulation identified specific equipment pieces requiring capacity increases and quantified the throughput impact of various investment options. This analysis enabled Mitchel Lincoln to prioritize capital investments based on capacity impact and return on investment calculations.
The scenario analysis revealed that achieving the 2 billion square feet target would require a combination of operational improvements and strategic investments. The simulation provided specific recommendations for the optimal combination of train optimization, press enhancements, and equipment additions needed to unlock the corrugator machine’s full capacity potential.
Strategic Optimization Roadmap
The simulation analysis produced a comprehensive roadmap prioritizing bottlenecks and investment opportunities across conversion, outbound flow, and internal material handling operations. The roadmap identified train movement decision logic and production planning as complementary performance levers that could stabilize flow and support capacity growth.
Phase 1 Recommendations focused on train optimization initiatives that could be implemented without significant capital investment. These improvements included intelligent routing algorithms, dispatch logic optimization, and garage utilization enhancements that would provide immediate throughput gains.
Phase 2 Initiatives addressed press capacity constraints through targeted equipment enhancements and scheduling optimization. The simulation identified specific press modifications and operational improvements that would eliminate secondary bottlenecks revealed after train optimization implementation.
Phase 3 Strategic Investments outlined equipment additions and facility modifications required to achieve full 2 billion square feet capacity utilization. The roadmap provided specific investment priorities based on capacity impact analysis and implementation complexity considerations.
Advanced Analytics Foundation
The simulation model established a foundation for ongoing optimization analysis and decision support. Mitchel Lincoln now possesses sophisticated analytical capabilities for evaluating operational changes, testing improvement initiatives, and optimizing resource allocation decisions. The model enables rapid scenario analysis without operational disruption, supporting continuous improvement initiatives and strategic planning processes.
The next phase of the project will leverage the established model to analyze interactions between train movement optimization and production planning systems. This advanced analysis will enable potential integration of smart train dispatch algorithms that determine optimal routing for each work-in-progress pack to maximize overall system flow.
Strategic Value and Implementation Success
The SimWell partnership demonstrates how advanced simulation technology transforms traditional manufacturing optimization approaches while delivering measurable strategic value. The collaboration between Mitchel Lincoln and SimWell illustrates the potential for discrete event simulation to address complex operational challenges in corrugated packaging manufacturing environments.
Innovation in Manufacturing Optimization
The successful development and deployment of the full-plant Simio model establishes Mitchel Lincoln as a leader in applying advanced simulation technology to corrugated manufacturing operations. The project’s innovative approach to modeling unlimited product variety within complex material handling systems creates new possibilities for understanding and optimizing packaging production operations.
The simulation model’s ability to accurately represent custom manufacturing processes while identifying specific optimization opportunities validates the potential for advanced analytics to transform traditional capacity planning approaches. Mitchel Lincoln has created a replicable framework that addresses the fundamental challenge of optimizing complex manufacturing systems with unlimited product variation.
Data-Driven Investment Strategy
The simulation analysis provided Mitchel Lincoln with confidence in their capacity expansion decisions, accurate bottleneck identification, and optimized investment prioritization that minimizes capital requirements while maximizing throughput gains. The ability to test multiple scenarios without operational disruption enabled informed decision-making about optimization strategies and resource allocation.
The project’s success reinforces the importance of sophisticated capacity planning analysis in corrugated packaging operations, where complex constraints and custom product requirements demand precise optimization to maintain competitive advantage. Mitchel Lincoln’s experience demonstrates that organizations willing to invest in advanced simulation capabilities can achieve superior operational outcomes while minimizing risks associated with capacity expansion investments.
Industry Leadership and Future Applications
Mitchel Lincoln’s implementation of advanced corrugated manufacturing simulation positions the company as a thought leader in applying simulation technology to packaging industry operations. The solution demonstrates how traditional operational challenges can be overcome through innovative technology integration and collaborative development approaches.
The project’s success provides a blueprint for other corrugated packaging manufacturers seeking to modernize their capacity planning and optimization capabilities while maintaining the flexibility required for custom manufacturing environments. Mitchel Lincoln has established new standards for what is possible in corrugated manufacturing through strategic application of simulation technology.
The partnership with SimWell illustrates the value of combining industry expertise with advanced simulation capabilities to create solutions that address real-world operational challenges. This collaborative approach has produced a solution that not only solves immediate capacity constraints but also creates new possibilities for operational optimization and manufacturing innovation in the corrugated packaging industry.