Industry 4.0 - Worksharing Optimization

Improving profitability of machined part portfolio through advanced analytical tools in the aerospace sector

The Context

Optimization of machining processes is key for any industrial company having manufacturing operations as its core business. At Sonaca, the machining of high added-value technical parts and components represents a major part in company’s total revenue. In a highly competitive market, characterized by small volume and thin margins, monitoring the actual engineering costs becomes critical to the management.

Recent acquisitions of production facilities across the globe (especially in the US) induce a revision of the worksharing processes. The portfolio of machined parts needs to be optimized to leverage local functional specialization and production assets at group level. A key goal today is indeed to improve the overall equipment effectiveness (OEE) which can be defined as how well a particular manufacturing unit performs relative to its designed capacity and resource consumption during the periods it runs.

The Challenge

Today, in comparison to industrial benchmarks, the overall utilization of facilities, time and material for manufacturing operations is not considered as being optimal at Sonaca. There is a gap between actual and ideal performance. However, to optimize the worksharing allocation and improve the profitability, one needs to take into account various constraints as the costing breakdown structure, the type of parts to produce, the input materials that are required, the machines’ features and specifications, the level of automation, the market segregation policies, the performance of the process, the integration and interoperability with linked processes (straightening, mechanical saturation, heat and surface treatments, etc.). Computing all these constraints into an optimal worksharing formula is not something easy to perform. It involves operational research, data science and mathematical capabilities which the firm does not own today.

Key Question & Goals

Based on the aforementioned elements, the key question for the research can be formulated as follows:

“How to improve the profitability of an industrial firm through the optimization of the worksharing procedure in a context of multiple production sites?”

From a managerial contribution standpoint, the main goals of the research project can be grouped in two streams, and will be to :

Strategy and financial improvement goals (work package 1)

  • Develop an optimization algorithm to simulate industrial scenarios and ease the worksharing decision process based on costing and technical comparison;
  • Exploit the available data on manufacturing quality and on product/process classification to enhance the worksharing process on a continuous basis;
  • Take into account the economical parameters (i.e., financial variables of each manufacturing site) that can lead to optimize the profitability (i.e., the model should demonstrate savings of 1% per year on a fixed turnover basis);
  • Simulate the market and contract evolution in a consolidated way.

Benchmark and Process improvement goals (work package 2)

  • Outline the pros and cons of each production line related to product features;
  • Propose ways to increase the availability of the equipment to reduce the marginal cost and the hourly rate;
  • Open further related opportunities in terms of big data-based predictive maintenance initiatives;
  • Open further related opportunities in terms of IoT-based cost accounting initiatives.

From a theoretical perspective, the main goals of the research project will be to make contribution to the following areas:

  • Develop a sales and operations planning (S&OP) framework for the worksharing decision process;
  • Model the underlying supply chain design and planning problem using mathematical programming techniques;
  • Develop exact or heuristic optimization algorithms for solving the considered problem that can be used as decision aid tools within the S&OP framework;
  • Develop tools to analyse available data in order to obtain more accurate parameter estimates (e.g., manufacturing cost and quality), which are to be fed to the optimization algorithms as inputs;
  • Develop techniques to consider the effects of possible variations from those estimates;
  • Develop tools to analyse performance of the production lines/workstations depending on the product features.


About Sonaca Group

As an aerospace company active in aerostructure services and products, Sonaca Group has one-stop shops and integrated teams of design and industrial professionals who can provide responsive solutions tailored to customers’ needs. Sonaca Group can offer the best price combination with the latest automation technologies, low cost country manufacturing facilities and worldwide engineering offices. Year after year, Sonaca Group is recognized by its customers as “best-in-class”​ for quality and delivery performance of reliable industrial solutions. Thanks to its global footprint, the company is close to customers, accompanying them from early design stages to in-service support, focusing on reducing overall costs.

About SRIW

The SRIW Group (Société Régionale d’Investissement de Wallonie) contributes to the economic development of the Walloon region through partial financing of companies or development projects located in Wallonia. It invests in growth, alongside private investors through loans and equity. As a reliable, professional and ambitious financial partner, the SRIW Group supports the projects belonging to the Industry4.0 applied research stream of the HEC Digital Lab.