140
Machines in CapEx-optimized operation
Production Validation and Optimization via Material Flow Simulation
A manufacturer of sensor heads must quickly increase its production output after the SOP (Start of Production) of a newly built plant. However, only limited machinery is available there for the fabrication of quality-sensitive products with a high R&D iteration rate. Together with EFESO, the plant digitized its entire manufacturing process:
A fully parameterizable simulation now maps more than 900 process steps, so that all relevant KPIs such as production output, throughput time, and buffer utilization can be validated. In addition, process interrelationships were optimized and synchronized, allowing production to be fine-tuned in a virtual environment. This enables the conservatively planned factory to keep pace with an extremely dynamic market and increase the number of units produced in line with demand.
Industry: Industrial Manufacturing
Service: Cost and Value Engineering
Service: Data & Ai
Service: Digital & Ai
Service: Factory Planning
Service: Manufacturing
Service: Smart Factory
Service: Supply Chain
Our Client
The company specializes in the production of sensor heads for industrial applications. It implemented a greenfield project at a site in Asia in order to meet customer requirements in the application area "distance measurement" with a new product variant.
+900
Process steps in the simulated lines
+50
Simulation parameters from process times to control concepts
The Challenge
After the SOP, the order target was reliably fulfilled, but the company’s customer now needed significantly more products in a short space of time. Therefore, the plant had to increase its output and quickly adjust its machine utilization and production planning. The main challenges were:
- Demanding production environment: The configuration of the machinery for the new plant was optimized for CapEx. Therefore, the number of 140 machines was strictly limited. At the same time, the production process contains sequences in which the same production sequence is repeated up to 16 times, whereby three "key machines" are constantly used. After the SOP, repeated errors and time-consuming coordination and corrections came up.
- Development of rule-based planning during the ramp-up: The project team created a new production and material flow plan at the same time as the production ramp-up. It developed and tested their rules for several product variants individually and in parallel operation. While the first product rolled off the line "under full load", the SOP of the second product also had to start within a year.
- Material flow planning according to machine requirements: In order to be able to react flexibly to future changes in product variants with process and system adjustments, machine requirements planning should also be carried out.
Real Results Achieved Together
Together with EFESO, the company created a solid, structured plan for the material flow of its production and validated the static forecast. This enables the factory to increase the output with the existing machinery.
12
"Golden Rules" implemented for production planning
10%
Increase in output confirmed
6
Critical parameters validated
Transformation Impact
- Sensitivity analysis: Which of the production parameters have a significant impact on the result? How stable are the planning forecasts of the simulation model, especially in dynamic areas?
- Combination of information levels: How do the planning dimensions "capacity of the plant" and "actual process list of the production process" relate to each other?
- Future-proof technology: Modeling with the cross-platform simulation software AnyLogic also enables a flexible and data-driven simulation environment for future changes to the plant / line layout.
Our Approach
The factory achieved significant results in a short space of time with EFESO. The decisive aspects were:
- Dynamic model creation: The machine requirement was determined from the sum of the process times. In order to ensure that there is still enough capacity available in the entire plant for smooth production in all possible scenarios, the project team calculated a flat-rate factor of 20% for “dynamic influences”. This assumption could be verified with the help of the simulation model. The simulation model forms mutually accumulating disturbances, such as spontaneous failures or material flow disturbances that influence each other.
- Technological adaptability: The choice of AnyLogic as a simulation tool allowed the project team to develop a customized simulation model. This is a discrete-event and customized representation of the customer’s production reality, based on a jointly maintained database with all the parameters included.
- Looking beyond the project: The simulation model is structured in such a way that it can be adapted independently by the customer without in-depth simulation knowledge of the parameters. This also ensures flexible (new) configurations of the line in the future.
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Optimize the Material Flow in Your Factory
- Identification of critical systems in the production process, evaluation of the effects of failures
- Creation of an individual, agent-based simulation model with interfaces to intralogistics planning, production planning and other areas
- Combination of the "plant capacity" and "actual process list of the production process" information levels
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