Alestis Aerospace is a leading company in engineering and manufacturing technologies for the assembly of aerostructures and one of the three TIER 1 companies operating in Spain, with an international presence and major innovative projects. Given its high production level and the importance of meeting deadlines in the sector, it is essential for Alestis to create optimal resource plans, both human and logistical, to ensure the timely achievement of milestones while promoting the efficient and effective use of these resources.
The planning process was predominantly manual. All the relevant data and constraints were recorded in Excel sheets, and generating a final plan could take hours, in addition to the costs associated with replanning. Given this scenario, what are the challenges set by the project?
- Automate the planning generation process, significantly reducing the personnel costs dedicated to it.
- Automatically and digitally integrate all the data and constraints applicable to a planning process (schedules, calendar, deadlines, availability, etc.).
- Implement multiple planning strategies based on the set business objectives (such as production in less time, reduction of downtime, etc.).
- Integrate the planning obtained in real-time and bidirectionally with the digital production control system to facilitate plant operations and track the progress of the ongoing work.
Modeling of constraints and strategies. Given the complexity of such a project, the first step was to digitally model and integrate the business constraints involved in the planning process (operators, calendars, shifts, production lines, availability, etc.); and to model and implement, through advanced mathematical methods, the strategies for calculating schedules based on the aforementioned constraints.
To achieve this, a central service-oriented module was implemented, which, on one hand, automatically absorbs the required data from various sources to carry out a planning process, and, on the other hand, calculates this planning optimally based on the indicated constraints and the selected strategy. This central module is based on Choco Solver technology, an open-source JAVA library for constraint programming.
A user-friendly tool. Once the core of the planner was obtained, it became essential to build a graphical environment that was friendly, usable, and simple, transforming the user experience from a complex and cumbersome problem into a more agile and intuitive task. To achieve this, a web application was designed and built, allowing the end user to manage restrictions, select strategies, launch the scheduling calculations, and visualize or even modify the resulting schedules on Gantt charts.
For the development of the website, connected in real-time with the central calculation system, Node.js is used. It is an open-source JavaScript framework designed to build scalable network applications. It is a library and event-driven I/O runtime, meaning it is asynchronous, running on the JavaScript interpreter itself.
Planning, especially in industrial environments, is crucial for production but involves high generation costs and presents significant complexity in achieving optimal results. Through solutions like the one presented, a remarkable improvement in production performance is achieved by applying optimized planning models based on business constraints and strategies.
More specifically, the following has been achieved:
- A significant reduction in planning costs derived from the reduction in time spent.
- An increase in efficiency and optimization of production resources derived from the quality of the calculated plans.
- Real-time integration with production and manufacturing management systems.
Alestis Aerospace is a leading company in engineering and manufacturing technologies for the assembly of aerostructures and one of the three TIER 1 companies operating in Spain, with an international presence and major innovative projects. Given its high production level and the importance of meeting deadlines in the sector, it is essential for Alestis to create optimal resource plans, both human and logistical, to ensure the timely achievement of milestones while promoting the efficient and effective use of these resources.
The planning process was predominantly manual. All the relevant data and constraints were recorded in Excel sheets, and generating a final plan could take hours, in addition to the costs associated with replanning. Given this scenario, what are the challenges set by the project?
- Automate the planning generation process, significantly reducing the personnel costs dedicated to it.
- Automatically and digitally integrate all the data and constraints applicable to a planning process (schedules, calendar, deadlines, availability, etc.).
- Implement multiple planning strategies based on the set business objectives (such as production in less time, reduction of downtime, etc.).
- Integrate the planning obtained in real-time and bidirectionally with the digital production control system to facilitate plant operations and track the progress of the ongoing work.
Modeling of constraints and strategies. Given the complexity of such a project, the first step was to digitally model and integrate the business constraints involved in the planning process (operators, calendars, shifts, production lines, availability, etc.); and to model and implement, through advanced mathematical methods, the strategies for calculating schedules based on the aforementioned constraints.
To achieve this, a central service-oriented module was implemented, which, on one hand, automatically absorbs the required data from various sources to carry out a planning process, and, on the other hand, calculates this planning optimally based on the indicated constraints and the selected strategy. This central module is based on Choco Solver technology, an open-source JAVA library for constraint programming.
A user-friendly tool. Once the core of the planner was obtained, it became essential to build a graphical environment that was friendly, usable, and simple, transforming the user experience from a complex and cumbersome problem into a more agile and intuitive task. To achieve this, a web application was designed and built, allowing the end user to manage restrictions, select strategies, launch the scheduling calculations, and visualize or even modify the resulting schedules on Gantt charts.
For the development of the website, connected in real-time with the central calculation system, Node.js is used. It is an open-source JavaScript framework designed to build scalable network applications. It is a library and event-driven I/O runtime, meaning it is asynchronous, running on the JavaScript interpreter itself.
Planning, especially in industrial environments, is crucial for production but involves high generation costs and presents significant complexity in achieving optimal results. Through solutions like the one presented, a remarkable improvement in production performance is achieved by applying optimized planning models based on business constraints and strategies.
More specifically, the following has been achieved:
- A significant reduction in planning costs derived from the reduction in time spent.
- An increase in efficiency and optimization of production resources derived from the quality of the calculated plans.
- Real-time integration with production and manufacturing management systems.