Approach for Increasing the Resource Efficiency for the Production Process of Titanium Structural Components

Titanium structural components for the aircraft industry are usually manufactured from ingots of primary material. The process chain for the fabrication of these components consists of the production of titanium sponge, the melting process, the forging process and the milling process. High chip removal rates from up to 95% due to the milling process and a high energy demand in producing the titanium sponge of about 85% of the overall energy consumption characterize the process chain. This obviously leads to a high optimization potential under monetary and energetic aspects. Recycling titanium chips for the ingot production could help to dramatically improve the overall production process in terms of ecological aspects. However, process-induced contaminations of the chips prevent the use of high amounts of these in the melting procedure. Macroscopic impurities like residues of cooling lubricant can be removed in a complex cleaning process. Yet, contaminations like oxidization cannot be eliminated, hence only a small amount of titanium chips is usable in the melting process to achieve the required purity of the titanium alloy. This paper describes a novel method to decrease the energy consumption in fabricating titanium products. By reducing process-induced contaminations, the amount of titanium chips usable in the melting process can be significantly increased and consequently the necessary quantity of titanium sponge reduced. The described method contains the investigation of relevant influencing factors like the impact of tool and cooling concept on chip quality or manufacturing costs. The research of cause-effect relationships identifies the trade-off between ecological and economic targets. A mathematical description of this relationship is implemented within a simulation environment to find an optimum between ecological and economic targets. The paper describes this approach with samples of the titanium alloy Ti6Al4 V.BMWi/03ET1174

Multi-Criteria Decision Support for Manufacturing Process Chains

During the manufacturing planning, multiple variants of process chains for the manufacturing of a product to be developed are generated by engineers. In order to select an optimal variant, multiple decision criteria specifying technical, ecological and economical properties of the process chains as well as multiple assessments of different domain experts have to be taken into account. The contribution of this article is a two-step approach that provides a multi-criteria multi-expert assessment of manufacturing process chains supporting the selection of an optimal process chain. A web-based software tool that implements the multi-criteria assessment of process chains is also presented

Improvement of a Genetic Algorithm for Manufacturing Optimization through Integration of Competence-based Criteria of the Working Personnel

Purpose: concept development and software modification to integrate worker´s competencies into technological process chain optimization using mathematical models and a genetic algorithm. Design/methodology/approach: A revision of GA applications found in literature is necessary for select the right strategy to change the process models. The competences and knowledge theory for the personnel give a systematic way for collecting the workers skills and the needed competence to perform the job. The development of a new coefficient, the KOP, gives the possibility of having a parameter that connects the workers´ competencies with every process: this coefficient guides the planner to do a better worker assignment of the workers to the jobs, and obtaining process parameter influenced by the personnel. This is obtaining by the insertion of coefficients in the process models, taking in consideration the influence of the personnel on the process time (different for every kind of job). The modifications of the prototype develop a method which allows for an integrated technological and competence-based process chain planning. This method was implemented into a software prototype by programming a “competence-module”. Findings: The changing of the process models gives as results of the GA a set of parameters influenced by the competence of the personnel, and a set of KOPs optimally selected by the algorithm: the evaluation of the competence owned and needed bring to a production of another KOPs set. The systematic confrontation of these two sets, with the introduction of logic passages and a tolerance system, bring to an optimal selection of the personnel. The result of the validation shows an improvement of the performances, in relationship with the available pool of worker. Originality/value: The proposed work can be considered as a first step to the simultaneous and symbiotic optimization of the process parameters and the working personnel system. This is a first proposal to integrate the personnel in a systematic way, contemporary for the influence on time, cost, and parameters of the processes and for the assignation to the jobs themselves. Keywords: personnel influence, competence based criteria, modified Genetic Algorithms, personnel interacting GUI Document type: Master Degree Thesis