Data Driven Process Optimization

Introduction

Aerospace product manufacturing and maintenance, repair and overhaul (MRO) production processes involve numerous complex and interconnect processes making the ability to predict performance difficult. Discrete event simulation can model a series of complex independent processes, and predict outcomes. The simulation imitates the time-dependent and stochastic behavior of real-world processes.

Performing and analyzing discrete event simulations allows the testing of the planned production system before or during production execution. The digital model allows users to run experiments and what-if scenarios without disturbing an existing production system. It can also be used in planning long before the real system is installed. Extensive analysis tools, statistics, and charts help users evaluate manufacturing scenarios and make fast, reliable decisions early in production planning.

MRO and manufacturing simulation helps MROs and manufacturers:

• Virtually commission production lines to detect and eliminate problems that otherwise would require cost and time-consuming corrective measures during production ramp-up

• Minimize the investment cost of production lines without jeopardizing the required output

• Optimize the performance and energy usage of existing production systems by taking measures that have been verified in a simulation environment, and benefits quantified, prior to implementation

Quantifying Value

The value derived from these process simulations can be quantified, and the simulations can be leveraged for many use cases.

1. Strategic Decisions

• Cost Savings from Process Changes: Estimate the reduction in operational costs by simulating and implementing more efficient workflows. For example, if a new workflow reduces labor hours by 15%, that translates into significant annual savings.

• Return on Investment (ROI) for Capital Expenditures: Show how simulations can predict the impact of new equipment or facility expansions, reducing the risk of underutilization or over-investment. This can help in quantifying potential gains in throughput and revenue.

• Time-to-Value: Demonstrate how much faster a company can realize benefits from strategic changes by simulating them first, reducing trial-and-error costs.

2. Tactical Decisions (day-to-day)

• Efficiency Gains: Quantify the improvement in daily or weekly throughput. For instance, if better resource allocation reduces downtime by 10%, you can translate that into dollar value based on increased production.

• Reduced Overtime and Labor Costs: By simulating staffing needs more accurately, you can show how much can be saved in labor costs.

• Minimized Disruptions: Quantify the financial impact of reduced downtime or faster response to unexpected issues, which can lead to higher overall equipment effectiveness (OEE).

Supply Chain Simulations

A supply chain simulation makes supply chain management dynamic by predicting the performance of the logistic network over time. The system takes the logical rules of the standard supply chain and executes it as a simulation and helps the user gain insight into the real behavior of the system. The supply chain simulation takes multiple factors into consideration, namely, customer order count, inventory storage and capacity, factory production capacity, the availability of supplier workers, materials availability, and much more.

Tool: Tecnomatix Plant Simulation

Although we can work with any manufacturing simulation software, our modeling tool of choice is Tecnomatix Plant Simulation,  a discrete event simulation software for production throughput analysis and optimization. Tecnomatix Plant Simulation allows us to model, simulate and optimize manufacturing and logistics systems and their processes. This simulation software produces extensive production statistics and key performance indicators (KPIs) required for in-depth analysis of predicted results.

Operationalizing Simulation Models

Advanced companies operationalize Tecnomatix Plant Simulation models using Mendix, low-code rapid application development platform via the Mendix, optimize my plant solution.

This capability allows the production process digital twin (the simulation) to be put in the hands of the plant managers and shop floor leaders to enable them to predict and optimize production processes in their day to day operations via a customized user friendly interface. This solutions capabilities include the ability to:

• Improve on-time delivery

• Improve equipment utilization

• Predict order delivery dates and optimize schedules

• Identify bottlenecks in the production processes

• Simplify simulation data collection and contextualization

See the potential? We can help

Skypath Analytics has years of experience building and operationalizing simulation models to improve aerospace manufacturing and MRO production performance. We can help you increase the speed to value, and leverage these powerful tools to improve your bottom line.

From data to decision. From complexity to clarity.