Over the past few years, at Itemsa we have worked with leading companies in the automotive industry such as EBRO Factory, SAS-Motherson, FICOSA and Magna Mirrors, helping their Process Engineering, Manufacturing, Quality and Logistics teams address one of the major challenges facing industry today: efficiently managing mixed-model manufacturing and variable production mix environments.
In this type of manufacturing environment, a single production line handles different models, variants or product configurations, each with different workloads at each workstation. This increasingly common scenario requires companies to go far beyond effective production organization.
This manufacturing model —which is by no means exclusive to the automotive industry— presents significant challenges, including component supply imbalances, the risk of production losses, quality issues, low operational efficiency and difficulties in production planning.
For this reason, the goal is no longer simply to get production right first time, but also to eliminate waste and reduce costs. Accurate, standardized and data-driven planning is also essential to enable fast decision-making whenever demand changes.
Why is mixed-model production so complex?
Mixed-model manufacturing has been a feature of the automotive industry for many years. However, the trend towards greater vehicle customization and shorter delivery times has significantly increased its complexity.
These environments have to manage several factors simultaneously:
- different product references manufactured on the same line;
- multiple options and variants;
- significantly different workloads between products at each workstation;
- constant fluctuations in demand;
- the need to maintain consistent quality and productivity standards.
When this information is not properly structured, companies often encounter difficulties in balancing production lines, planning resources, calculating capacity or anticipating the impact of production changes.
The key: a common language across the entire organization
In our experience, the real challenge is not simply calculating times or balancing a production line.
The major challenge is ensuring that the entire organization works with the same information, using the same criteria and a single process knowledge database.
Knowing exactly how the workload of each product or product family has been planned, analyzed and calculated, determining which line it should be manufactured on, and being able to drill down to the highest level of detail through a high degree of standardization is an objective pursued by most manufacturers today.
When all departments —Process Engineering, Manufacturing, Logistics, Quality and Industrialization— share this common language, decisions can be made much faster and with greater reliability.
Moving from Excel to a single database
It was precisely this need that led us to develop Approductivity. This suite is much more than a calculation tool: it is a platform that centralizes all production process information within a single, standardized database.
By developing a detailed understanding of the product, manufacturing environment, standard times (time studies, MTM, etc.), quantities required to meet demand (Takt Time), operations, resources, materials and manufacturing configurations, teams can:
- calculate optimized line balances;
- simulate different production scenarios;
- adjust resources and operator numbers;
- analyze different demand volumes;
- assess new layouts or reorganizations;
- plan production capacity much faster.
As a result, engineers no longer need to spend hours working with complex spreadsheets and can focus their time on what truly adds value: improving processes.
Proven results across the automotive industry
The implementation of Approductivity in recent years has steadily consolidated its presence among major automotive manufacturers.
Companies such as SAS-Motherson, with an international presence in more than twenty countries, FICOSA, Magna Mirrors and EBRO Factory already use our technology to further standardize their processes and establish a common methodology for production planning and analysis.
Particularly in organizations with multiple plants or production sites, having a single approach to calculating times, line balances and workloads —while also being able to share and compare performance and efficiency indicators— greatly facilitates knowledge transfer and ensures that every team works according to the same criteria and towards the same challenges.
Up to a 30% improvement in productivity
Based on our experience with implementation projects, using Approductivity can deliver productivity improvements of between 20% and 30%, depending on each organization’s starting point.
Beyond the percentage improvement itself, however, the main benefit lies in the ability to make decisions based on reliable data, simulate scenarios before implementing them, and work with a single, global and standardized system that can support the company’s growth.
Our approach to industrial optimization
At Itemsa, we do not see optimization as a collection of isolated calculations.
Our objective is to structure and optimize operations so that the entire organization shares a common way of working, a single database and one source of truth for production process information.
Approductivity —backed by 40 years of accumulated know-how— is our technical response to a challenge shared across much of the industrial sector: turning fragmented data into actionable knowledge for better decision-making.
If you think we can also help your company improve its competitiveness and productivity, contact us!
