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.

Today, for the enterprises, the competition is more and more intense and more competitor try to satisfy their customers. In the field of automotive industry, the demands for the product increase and the company need to satisfy the demand. As the demands increases, the company should produce more product than usual. In the same time the comfort and health of the workers should be consider. Some factors such as workstation design should take into consideration in order to increase the productivity and at the same time protect workers from accidents and health problem. Therefore, the workstations need to be redesign by applying the ergonomics principles. This paper presents the combined application of Artificial Neural Networks and the Rapid Upper Limb Assessment (RULA) Analysis in the process of redesign ergonomic workstations. Artificial Neural Networks excel in gathering difficult non-linear relationships between the inputs and outputs of a system. We used, in this work, a feed forward neural network in order to ranking a workstation. The neural network is simulated with MATLAB. The experiment presented in this paper was realized at University of Piteşti, Faculty of Mechanics and Technology, Department of Manufacturing and Industrial Management, using CATIA V5 software.

Abstract. Control methods specific to pull flow are based on firm customer orders, so market demand dictates production and initiates a chain of requests, as a reactive event, in planning the material requirements and the production cycle. For this reason, the objective of the research in this paper was to determine the impact of Kanban, Conwip and Base stock methods to control a production system, in terms of input variables in between certain limits on the output performance indicators of the production system. The analysis of the cost pointed out the fact that production control methods have a significant influence on this indicator of production.

The main aim of Lean Manufacturing concept is to produce more with less: space, stock, workforce and time. The companies that along the years implemented Lean Manufacturing, reached a spectacular development, mainly because with the same workforce and financial resources, succeeded to increase significantly their profit (some reached up to 300-400% increase). The strength of Lean concept is the calculation of value of product for the final client, considering each stage of manufacturing. Therefore, the main aim of this paper is to analyze and improve the manufacturing flow of a component, from the system entry point to its exit using Flow Mapping and Value Stream Mapping. After all the actions on improving the flow, the activities without added value decreased with 15.92% and the lead time with 15.61%

The challenges of choosing methods of material flow control are bigger due to the fact that they authorize the quantity of production in each processing stage so that the products get to the customer at the right moment and in the quantity wanted, while minimizing the costs and stocks of the production system. For this reason, the objective of the research performed in this paper is to determine the impact of Kanban control methods on the performance indicators, total cost and interoperation stock of a production system, given the fact that many system parameters are variable. The main conclusion drawn from the results is that when the input parameters vary within certain limits the control method with the best performance indicators for a production line can be established following the methodology used in this paper. Methodology is a useful tool in the hand of those who design production systems because it allows the choice of the control method which provides the best performances, at least from the viewpoint of two indicators: costs and stocks.