Lean Manufacturing includes an ensemble of methods to analyze and continuously improve the functioning of manufacturing systems. The research presented in the literature highlights the fact that these methods are, on their own, in a process of continuous improvement as tools, being used in different ways, for different production systems. The paper presents an algorithm that facilitates the choice of the performance evaluation method, and the choice of the method of improvement that needs to be implemented for an efficient analysis and for a continuous increase of the manufacturing system performance. In addition to these, for the JobObservation and 5S methods, chartflows are proposed and specific tools are developed (questionnaires, forms etc.) that are meant to facilitate the implementation and to focus (guide) the user in the direction of improvement for the analyzed process. The algorithm, techniques, and tools developed in this research were used in a case study that took place in a production system “plastic injection”. Thus, a series of important improvements were made in the functioning of the production system, consisting of the reduction of production area, decrease of cycle time, decrease of the number of operators, stabilization, standardization, and securing of the work processes. All this has led to the improvement of several key performance indicators (KPIs) of the production system. The analysis of the investment in the reorganization of the production system in relation to the obtained gains shows a payback of approximately 1 month, proving the efficiency of use in such a form of the Lean Manufacturing methods.

Globalization of production and strong competition in the economic environment requires manufacturers from automotive industry to offer their customers a wide range of products, of the best quality and at lower prices. In order to achieve a competitive advantage, the automotive industry must to adapt their production systems to mass customisation, so that they can provide the variety demanded by the customers while limiting their costs and maintaining their profitability. In this context, research to increase the performance of assembly lines is increasingly numerous and use different techniques, as: layout design, mathematic modeling, dynamic simulation, Lean manufacturing etc. This paper presents a methodology for improving production flows on an assembly line, which was developed to provide the designer and manager of assembly lines in the automotive industry with a set of logically related steps and steps that would allow to achieve a high-performance assembly line. The stages and steps of this methodology consist in the use of methods from different fields, such as: layout design, modelling-simulation of production flows, labour study, lean manufacturing, and for their application different techniques and tools are used.

The simulation is almost always used as an integrated part of a system design process, as method to identify the improvements of an existing process, to evaluate an already developed model to find alternative solution for it or to compare working hypothesis. It represents an experimental technique that allows experimentation on models of the real system created using a specific simulation language. The knowledge accumulated during the experimentation on the model can be useful and applicable on the real system. Considering that, when it comes to talking about modelling and simulation it is talked about building a model of a real system and the experimentation possible on it. In this paper we will experiment a methodology to simulate the operating mode of a production system from the automotive industry, formed of several interconnected stages. The techniques and instruments used to make the activities in this methodology are in the fields of flow analysis and comparative analysis.

Considering the dynamic environment in which the present companies work, global market, fierce competition, frequent changes of techniques and technologies, more diverse demand from clients, changing norms and ethics, it is a pressure that rises. To cope with these complex factors, the modelling and simulation of production systems became a main approach in the middle of 20th century. To develop a model and to later use it in simulation is an “artistic” balancing of opposites that demand finesse and skills; on one side the model must be easy to use, that meaning it must involve a level of abstraction from reality, on the other side the model must be a faithful representation of the system it mimics. Therefore, in this article we will develop a learning platform for a methodology to use the modelling and simulation in the analysis of production systems performances. The platform and the methodology will be later experimented and validated, leading to a higher level of research quality.