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AD 2000

Definition: The AD 2000 code is a German technical code for the design, calculation and manufacture of pressure vessels. It is regarded as a recognised rule of technology in pressure equipment construction.

Additive Manufacturing

Definition: Additive manufacturing (AM) is an industrial production process in which components are built up layer by layer from digital 3D data. The geometry is created through targeted material deposition or selective melting, not through material removal. Terminology and process classification are defined in DIN EN ISO/ASTM 52900.

Practical relevance: Industrially relevant processes include Laser Powder Bed Fusion (LPBF/SLM), Electron Beam Melting (EBM), Binder Jetting and Fused Deposition Modeling (FDM). Quality criteria include component density (>99 % for metal AM), porosity, surface roughness (Ra), dimensional accuracy and mechanical properties to DIN EN ISO 6892 (tensile test). Process parameters, powder quality and heat treatment influence the microstructure, residual stresses and fatigue behaviour.

Decision-making perspectives:

Technical decision-makers: process stability, anisotropy, residual stresses, qualification of build processes and components.
Purchasing/project management: specification of material, build parameters, test certificates (e.g. EN 10204 3.1) and acceptance criteria.
Science: microstructure-process correlation, validation to the ISO/ASTM 529xx series.
Insurance/law: traceability of process data, documentation obligations, product liability.

Typical testing or verification methods: computed tomography (CT), tensile test, hardness testing, metallography, non-destructive testing (NDT).

FAQ:

Which standard defines additive manufacturing?
DIN EN ISO/ASTM 52900 defines the terminology and fundamental process categories of additive manufacturing.

Aggressive Media

Definition: Aggressive media are chemical or physico-chemical substances that can damage materials through corrosion, stress corrosion cracking, hydrogen uptake or erosion. These include acids, alkalis, chloride-containing solutions, high-temperature water and hydrogen-bearing process atmospheres. The assessment takes into account temperature, pressure, concentration and flow conditions.

Practical relevance: In chemical plants, power stations, offshore or pressure-equipment systems, aggressive media decisively determine the material selection and the corrosion-protection concept. Key parameters are the corrosion rate (mm/year), pitting potential, pH value, redox potential and material properties in accordance with DIN EN ISO 8044. Incorrect assessments can lead to leaks, HTHA damage or premature component failure.

Decision-making perspectives:

Technical decision-makers: selection of suitable alloys, coatings or cathodic protection systems under defined operating parameters.
Purchasing/project management: definition of resistance verifications, specifications and test requirements in the requirement specification.
Science: analysis of electrochemical mechanisms, polarisation curves, long-term exposure tests.
Insurance/law: proof of standard-compliant material selection, documentation of the risk and hazard assessment.

Typical testing or verification methods: corrosion testing, salt spray test (DIN EN ISO 9227), electrochemical polarisation measurements, materials analysis.

FAQ:

How is resistance to aggressive media assessed?
Through standardised laboratory tests, field tests and the quantitative determination of the corrosion rate under defined boundary conditions.

AI-assisted materials analysis

Definition: AI-assisted materials analysis refers to the use of machine learning and artificial intelligence methods for the automated evaluation of materials data. This includes image analysis of microstructures, spectral data or process parameters. The aim is to identify patterns, anomalies and correlations with mechanical properties.

Practical relevance: Applications include automated microstructure classification (e.g. SEM/EBSD images), prediction of material properties, early failure detection and optimisation of additive manufacturing processes. The prerequisites are validated datasets, defined training models and transparent validation metrics. Insufficient data quality can lead to erroneous forecasts.

Decision-making perspectives:

Technical decision-makers: Use of data-based models for process monitoring and quality forecasting.
Purchasing/project management: Assessment of software solutions with regard to validatability and integration capability.
Science: Development of explainable models (Explainable AI) and statistical validation.
Insurance/law: Traceability of algorithmic decisions and documentation of training data.

Typical testing or verification methods: Image classification using neural networks, regression models, validation by reference tests and statistical metrics (e.g. accuracy, RMSE).

FAQ:

Can AI replace classical materials testing?
No, AI complements existing testing methods but does not replace physical validation through standard-compliant tests.

Analysis of Manufacturing Processes

Definition: The analysis of manufacturing processes is the systematic examination of production sequences to assess stability, reproducibility and quality capability. The aim is to identify the causes of deviations on the basis of statistical indicators and technical parameters. Quality management systems such as ISO 9001 form the basis.

Practical relevance: Key parameters are process capability indices (Cp, Cpk), reject rate, tolerance compliance and repeatability. Methods such as Statistical Process Control (SPC), Failure Mode and Effects Analysis (FMEA) and Measurement System Analysis (MSA) serve to minimise risk. Documented process monitoring is mandatory in regulated industries (e.g. automotive, pressure equipment).

Decision-making perspectives:

Technical decision-makers: evaluation of critical process parameters and validation of series releases.
Purchasing/project management: supplier audits, definition of quality agreements and acceptance criteria.
Science: statistical modelling, analysis of variance and process simulation.
Insurance/law: proof of proper production monitoring in the event of liability.

Typical testing or verification methods: process capability analysis, audit reports, test equipment monitoring, SPC documentation.

FAQ:

What does a Cpk value of 1.33 mean?
A Cpk ≥ 1.33 is often regarded as the minimum requirement for a statistically capable and sufficiently stable process.

ASME

Definition: ASME (American Society of Mechanical Engineers) publishes technical codes and standards, in particular the Boiler and Pressure Vessel Code (BPVC). This defines requirements for the design, materials, manufacture and testing of pressure equipment.

Practical relevance: The ASME BPVC is recognised worldwide and forms the basis of many international plant projects. It contains specific requirements for materials, welding procedures and NDT.

ASTM

Definition: ASTM (ASTM International, formerly the American Society for Testing and Materials) is a globally recognised standardisation organisation that develops technical standards for materials, testing methods and products. ASTM standards define requirements for chemical composition, mechanical properties and testing methods. They are particularly authoritative in the North American market.

Practical relevance: ASTM standards such as ASTM A516 (pressure vessel steel) or ASTM E1820 (fracture mechanics) are used internationally. They govern testing conditions, specimen geometries and acceptance criteria. In global projects, ASTM standards are frequently applied in parallel with EN or ISO standards.

Decision-making perspectives:

Technical decision-makers: Ensuring internationally comparable material and testing criteria.
Purchasing/project management: Contractually clear specification for export and US projects.
Science: Comparability of test results worldwide.
Insurance/law: Reference framework in international liability cases.

FAQ:

Where are ASTM standards mainly applied?
Primarily in the USA, but increasingly also in international industrial projects.

ASTM E1820 – Fracture Mechanics Testing

Definition: ASTM E1820 is a US testing standard for determining the fracture toughness of metallic materials. It describes procedures for determining parameters such as K_Ic, J-integral (J_Ic) and CTOD. The standard is central to the fracture mechanics assessment of components containing cracks.

Practical relevance: ASTM E1820 defines specimen geometries (CT, SENB), pre-cracking, loading rate and evaluation methods including R-curves. It is used in pressure equipment construction, in aviation and in the energy industry. Results feed into fitness-for-service analyses and service-life assessments.

Decision-making perspectives:

Technical decision-makers: Assessment of critical crack sizes and safety margins.
Purchasing/project management: Specification of fracture mechanics parameters in international projects.
Science: Comparison with ISO 12135 and validation of crack growth models.
Insurance/law: Verification of standard-compliant fracture toughness testing.

Typical testing or verification methods: CT and SENB specimens, J-R curves, CTOD determination.

FAQ:

Which parameters are determined according to ASTM E1820?
K_Ic, J_Ic and CTOD for assessing crack toughness.