Precise sustainability assessment becomes increasingly important in decision-making, marketing, and regulations. Therefore, reliable and comparable LCA becomes mandatory. Currently, primary data is rarely available due to vastly complex value chains. Secondary data from eco-databases provide a remedy to estimate the sustainability impacts of up- and downstream processes. While giving insights and estimations, this data is seldom fitting exactly to the own processes and lacks comparability. Therefore, this paper proposes a method to close the gap between unreliable secondary data and unavailable primary data. This gap is to be closed by the integration of simulated process data. CAM is a tool during the work preparation to assess the design's manufacturability, decrease set-up times and optimize the NC code. However, integrating DES into LCA is still subject to research and will be discussed in this paper. This paper answers the question of the necessary steps to integrate the simulated production process in an LCA to increase the quality and reliability of sustainability indicators. A method is presented, and the implementation of the steps with the help of a developed assistance system on an example is performed.

Manufacturing of high-quality components and assemblies is clearly recognised byindustrialised nations as an important means of wealth generation. A “right first time”paradigm to producing finished components is the desirable goal to maximise economicbenefits and reduce environmental impact. Such an ambition is only achievable through anaccurate model of the machinery used to shape the finished article. In the first analysis,computer aided design (CAD) and computer aided manufacturing (CAM) can be used to producean instruction list of three-dimensional coordinates and intervening tool paths totranslate the intent of a design engineer into an unambiguous set of commands for amanufacturing machine. However, in order for the resultant manufacturing program toproduce the desired output within the specified tolerance, the model of the machine has tobe sufficiently accurate. In this paper, the spatial and temporal sources of error andvarious contemporary means of modelling are discussed. Limitations and assumptions in themodels are highlighted and an estimate of their impact is made. Measurement of machinetools plays a vital role in establishing the accuracy of a particular machine andcalibrating its unique model, but is an often misunderstood and misapplied discipline.Typically, the individual errors of the machine will be quantified at a given moment intime, but without sufficient consideration either for the uncertainty of individualmeasurements or a full appreciation of the complex interaction between each independentlymeasured error. This paper draws on the concept of a “conformance zone”, as specified inthe ISO 230:1 – 2012, to emphasise the need for a fuller understanding of the complexuncertainty of measurement model for a machine tool. Work towards closing the gap in thisunderstanding is described and limitations are noted.