Lean et industrie du futur : regards croisés sur la productivité des PME manufacturières.
A global national project concerning French Aeronautic Business started in France in 2014, after one year of preparation and alignment between all stakeholders. The target was to support the Operational Performance improvement of French Aeronautic SMEs (Small and Medium Enterprises). A total of 401 companies were supported with a common methodology. A cluster with a supportive approach was selected to engage both suppliers and customers. Local and regional economical stakeholders were also included. This supportive method was innovative as several SMEs (not competitors) were supported at the same time and in the same region with the same facilitator and for the same customer. To leverage the workload, several waves were organized between 2014 and 2016. The current publication summarizes the results of 306 companies of the original 401 companies. The support of the last waves of companies were finished when the analysis shared in the current document was published.
Lean is an approach that aims to eliminate waste in production activities. Recognized by companies, this approach yields significant gains in the short term. However, at medium and long term, these results have limitations. Our research work is focused on overcoming these limitations. So we studied the performance model adopted by the managers of Lean companies and the mental representations that underlie this model. In this paper, we support our research on a case study based on interviews with companies applying Lean approach and having met the mentioned limits. We then propose a new Lean performance model that attempts to overcome such limitations. This model is based on the vision that production operators contribute to the performance of the company through the creation and deployment of relevant operating modes during their work in Lean context. We also propose a modelling framework that allows to represent the impact of this new Lean performance model on the decision making in a Lean production system.
Information and communication technologies (ICT) are radically transforming the company’s organization and their way of work. Open innovation practices such as crowdsourcing are largely based on digital media. However, to our knowledge, little work focused on how digital technology can affect the adoption of open innovation. Based on four previous studies, this article examines the correlation between open innovation practices developed by SMEs and digital integration within Germany, Italy, Korea and the United Kingdom. The goal is to understand whether there is a link between digital integration in an environment and the adoption of open innovation in SMEs. The results highlight that open innovation practices are not adopted in a similar way in each environment, and from a digital point of view, the adoption of each practice corresponds to different environments.
The need for companies to differentiate themselves in the global market is becoming increasingly important with the growing lack of manpower and the growth of competition accentuated by the arrival of digital technologies in the industrial, logistic and commercial environment. Companies of all sizes are moving towards Industry 4.0. Quebec manufacturing SMEs, however, seem to lag behind in the digital transformation of their organization and processes. This research project aims to present the state of Quebec manufacturing SMEs at the digital level and to identify a relevant method and the most appropriate tools to encourage Quebec manufacturing SMEs to move efficiently towards a 4.0 environment. An analysis of the review of literature and experiences in Quebec shows that despite the lack of resources, the flexibility, the agility and the proximity to the customers are the main characteristics of Quebec manufacturing SMEs. The use of tools that accelerate effective decision-making and improve the relationship with customers therefore seem to be favoured in this type of environment.
The evolution of data mining techniques, as well as the increase in storage and computing capacity, in all areas, is generating interest of the data produced. In this way, manufacturing is no exception. Given the amount of data created when writing the various programs to be played on CNC machines, the application of data mining techniques to capitalize industrialization knowledge is considered. This paper concerns the structuring of an Industrialization Knowledge Base system, able to provide a programmer decision support, based on a corpus of documents relating to the machining of parts produced in the past, and thus assisting him in the production of a new part. The system uses data mining techniques to extract this information and deliver it to the programmer.