The optimal management of the manufacturing processes is achieved through a set of optimal decisions, which must be made for choosing the best way to follow, every time we find ourselves in a point from which several potential manufacturing paths start. A dedicated method, namely the Holistic Optimization Method has been already developed in this purpose, and validated in a number of studies based on artificial and real instances databases. In the current papers that approach the optimal management of the manufacturing processes, in order to estimate the consequences of a decision, are used known methods, such as: NN modeling, big data analysis, statistics, etc. In all these cases, the database size plays an essential role in terms of estimation quality. The present study aims to prove the feasibility of applying the Holistic Optimization Method when the decision-maker does not dispose of a consistent database. This can be a significant advantage relative to the other methods. The study is performed using an artificially generated instances database in the case of a turning process, and the results obtained are promising.

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In the global market, the supply chain performances have a significant impact on the company’s business strategy. The quality requirements that must be followed by suppliers require permanent monitoring of processes of design, development, production, installation and service of products through audits qualified based on supply chain management. This paper presents an analysis of the supplier qualification process including the main phases as follows: evaluation, monitoring and auditing of suppliers in supply chain management. Internal quality audits and/or suppliers are one of the key instruments for ensuring sustainability and performance in supply chain management. Auditing of suppliers is a core component of the modern management of suppliers, with the help of which the customer can analyze precisely relevant processes to existing or potential suppliers. Supplier audits help both commercial partners to increase the transparency of the supply chain and also simplify supplier selection, evaluation, monitoring and development. The suppliers must meet the highest quality standards for products and processes. The main purpose of this paper is to give a general view of the supplier qualification process which involves the steps from initial identification until the inclusion of the supplier in the Approved Supplier List (LST). This list should be managed in such way that a complete traceability is assured. Following the proposed qualification diagram the customer can obtain an image about the status of one supplier, can also identify the weak points considering the evaluation, monitoring and audit class.

There are several severe plastic deformation processes that transform the material from microsized grains to the nanosized grains under large deformations. The grain size of a macrostructure is generally 300 μm. Following severe plastic deformation it can be reached a grain size of 200 nm and even less up to 50 nm. These structures are called ultrafine grained materials with nanostructured organization of the grains. There are severe plastic deformation processes like equal angular channel, high pressure torsion which lead to a 200 nm grain size, respectively 100 nm grain size. Basically, these processes have a common point namely to act on the original sized material so that an extreme deformation to be produced. The severe plastic deformation processes developed until now are empirically-based and the modeling of them requires more understanding of how the materials deform. The macrostructural material models do not fit the behavior of the nanostructured materials exhibiting simultaneously high strength and ductility. The existent material laws need developments which consider multi-scale analysis. In this context, the present paper presents a laboratory method to obtain ultrafine grains of an aluminum alloy (Al-Mg) that allows the microstructure observations and furthermore the identification of the stress–strain response under loadings. The work is divided into (i) processing of the ultrafine-grained aluminum alloy using a laboratory-scale process named in-plane controlled multidirectional shearing process, (ii) crystallographic analysis of the obtained material structure, (iii) tensile testing of the ultrafine-grained aluminum specimens for obtaining the true stress-strain behavior. Thus, the microscale phenomena are explained with respect to the external loads applied to the aluminum alloy. The proposed multi-scale analysis gives an accurate prediction of the mechanical behavior of the ultrafine-grained materials that can be further applied to finite element modeling of the microforming processes.