Materials data is a critical resource for manufacturing organizations seeking to enhance products, processes and, ultimately, profitability. This data describes the properties and processing of the materials that these organization uses - metals, alloys, plastics, composite materials, ceramics, etc. This data may come from a wide range of sources - e.g., materials testing, quality assurance, or measurement of product performance. The process by which manufacturers manage and use such information is one essential 'cog' in the larger machine that is the product lifecycle.
One project that has looked at this issue in-depth is the Material Data Management Consortium (MDMC), [1] a collaboration of leading aerospace, defense, and energy enterprises - organizations such as NASA, Boeing, Rolls-Royce plc, Honeywell, and GE Aviation. The MDMC has identified the problems caused by failures in the materials data management process and investigated how an optimized process can lead to better innovation and quality.
Problems typically relate to productivity and data integrity. They begin with difficulties in consolidating specialized data stored in disparate sources and varied formats. Problems continue with the challenge of controlling and using approved information effectively throughout an organization, often within complex processes. These include:
This final issue ('traceability') is particularly important in quality and safety-conscious industries (such as aerospace or medical devices) where engineers need to be able to trace the full pedigree for a manufactured component - ideally, not just back to the design, but to all of the raw (materials and other) data used to create the design. This need for traceability has been a key driver for many commercial materials data management projects.
Materials data management is not just about the avoidance of problems and risk. The MDMC reports that best practice materials data management can have very positive effects on innovation and quality. For example, Rolls-Royce Aerospace have described how the ongoing assessment and analysis of all of the materials property information generated across the testing and design process can allow an organization to continually refine the 'allowable' values used in design, leading to improved product performance. [2]
Materials data management practitioners usually emphasize the need for a holistic approach. It is of limited use having a superb means to capture test data if that data disappears into a ‘black hole’ database that no-one accesses. Materials property analysis is a wasted investment if the results generated are not deployed effectively to the engineers who need to use them.
One way to itemize such issues is to examine each stage in the full materials data lifecycle. The MDMC sees this process as having four stages: capture, analyze, deploy, and maintain. Key issues at each stage are:
CAPTURE
| ANALYZE
|
DEPLOY
| MAINTAIN
|
These issues need to be addressed through a combination of good practice, robust processes, and appropriate information systems. MDMC members use a particular commercial-off-the-shelf (COTS) software solution. [3] Whether an engineering enterprise applies such a solution or builds an in-house system, it needs to account for the issues above and to integrate into its wider product lifecycle management (PLM) systems.
Systems engineering is an interdisciplinary field of engineering and engineering management that focuses on how to design, integrate, and manage complex systems over their life cycles. At its core, systems engineering utilizes systems thinking principles to organize this body of knowledge. The individual outcome of such efforts, an engineered system, can be defined as a combination of components that work in synergy to collectively perform a useful function.
Configuration management (CM) is a systems engineering process for establishing and maintaining consistency of a product's performance, functional, and physical attributes with its requirements, design, and operational information throughout its life. The CM process is widely used by military engineering organizations to manage changes throughout the system lifecycle of complex systems, such as weapon systems, military vehicles, and information systems. Outside the military, the CM process is also used with IT service management as defined by ITIL, and with other domain models in the civil engineering and other industrial engineering segments such as roads, bridges, canals, dams, and buildings.
Interoperability is a characteristic of a product or system to work with other products or systems. While the term was initially defined for information technology or systems engineering services to allow for information exchange, a broader definition takes into account social, political, and organizational factors that impact system-to-system performance.
The following outline is provided as an overview of and topical guide to software engineering:
In product development and process optimization, a requirement is a singular documented physical or functional need that a particular design, product or process aims to satisfy. It is commonly used in a formal sense in engineering design, including for example in systems engineering, software engineering, or enterprise engineering. It is a broad concept that could speak to any necessary function, attribute, capability, characteristic, or quality of a system for it to have value and utility to a customer, organization, internal user, or other stakeholder. Requirements can come with different levels of specificity; for example, a requirement specification or requirement "spec" refers to an explicit, highly objective/clear requirement to be satisfied by a material, design, product, or service.
Engineering management is applied engineering. It is the application of engineering methods, tools, and techniques applied to business management systems. Engineering management is a career that brings together the technological problem-solving ability of engineering and the organizational, administrative, legal and planning abilities of management in order to oversee the operational performance of complex engineering-driven enterprises. Careers positions include engineering manager, project engineer, product engineer, service engineer, process engineer, equipment engineer, maintenance engineer, field engineer, technical sales engineer, quality and safety engineer. Universities offer bachelor degrees in engineering management. Programs cover courses such as engineering management, project management, operations management, logistics, supply chain management, engineering law, value engineering, quality control, quality assurance, six sigma, quality management, safety engineering, systems engineering, engineering leadership and ethics, accounting, applied engineering design, business statistics and calculus. A Master of Engineering Management (MEM) is sometimes compared to a Master of Business Administration (MBA) for professionals seeking a graduate degree as a qualifying credential for a career in engineering management.
In systems engineering, information systems and software engineering, the systems development life cycle (SDLC), also referred to as the application development life cycle, is a process for planning, creating, testing, and deploying an information system. The SDLC concept applies to a range of hardware and software configurations, as a system can be composed of hardware only, software only, or a combination of both. There are usually six stages in this cycle: requirement analysis, design, development and testing, implementation, documentation, and evaluation.
In industry, product lifecycle management (PLM) is the process of managing the entire lifecycle of a product from its inception through the engineering, design and manufacture, as well as the service and disposal of manufactured products. PLM integrates people, data, processes, and business systems and provides a product information backbone for companies and their extended enterprises.
Product data management (PDM) is the name of a business function within product lifecycle management (PLM) that denotes the management and publication of product data. In software engineering, this is known as version control. The goals of product data management include ensuring all stakeholders share a common understanding, that confusion during the execution of the processes is minimized, and that the highest standards of quality controls are maintained. PDM should not be confused with product information management (PIM).
In the context of software engineering, software quality refers to two related but distinct notions:
Reliability engineering is a sub-discipline of systems engineering that emphasizes the ability of equipment to function without failure. Reliability describes the ability of a system or component to function under stated conditions for a specified period of time. Reliability is closely related to availability, which is typically described as the ability of a component or system to function at a specified moment or interval of time.
Digital Prototyping gives conceptual design, engineering, manufacturing, and sales and marketing departments the ability to virtually explore a complete product before it's built. Industrial designers, manufacturers, and engineers use Digital Prototyping to design, iterate, optimize, validate, and visualize their products digitally throughout the product development process. Innovative digital prototypes can be created via CAutoD through intelligent and near-optimal iterations, meeting multiple design objectives, identifying multiple figures of merit, and reducing development gearing and time-to-market. Marketers also use Digital Prototyping to create photorealistic renderings and animations of products prior to manufacturing. Companies often adopt Digital Prototyping with the goal of improving communication between product development stakeholders, getting products to market faster, and facilitating product innovation.
Femap is an engineering analysis program sold by Siemens Digital Industries Software that is used to build finite element models of complex engineering problems ("pre-processing") and view solution results ("post-processing"). It runs on Microsoft Windows and provides CAD import, modeling and meshing tools to create a finite element model, as well as postprocessing functionality that allows mechanical engineers to interpret analysis results. The finite element method allows engineers to virtually model components, assemblies, or systems to determine behavior under a given set of boundary conditions, and is typically used in the design process to reduce costly prototyping and testing, evaluate differing designs and materials, and for structural optimization to reduce weight.
Medical equipment management is a term for the professionals who manage operations, analyze and improve utilization and safety, and support servicing healthcare technology. These healthcare technology managers are, much like other healthcare professionals referred to by various specialty or organizational hierarchy names.
Manufacturing execution systems (MES) are computerized systems used in manufacturing to track and document the transformation of raw materials to finished goods. MES provides information that helps manufacturing decision-makers understand how current conditions on the plant floor can be optimized to improve production output. MES works as real-time monitoring system to enable the control of multiple elements of the production process.
In software engineering, a software development process or software development life cycle (SDLC) is a process of planning and managing software development. It typically involves dividing software development work into smaller, parallel, or sequential steps or sub-processes to improve design and/or product management. The methodology may include the pre-definition of specific deliverables and artifacts that are created and completed by a project team to develop or maintain an application.
Industrial engineering is an engineering profession that is concerned with the optimization of complex processes, systems, or organizations by developing, improving and implementing integrated systems of people, money, knowledge, information and equipment. Industrial engineering is central to manufacturing operations.
A First Article Inspection (FAI) is a production validation process for verifying that a new or modified production process produces conforming parts that meet the manufacturing specification detailed in technical or engineering drawings. Typically, a supplier performs the FAI and the purchaser reviews the report. The FAI process usually consists of fully testing and inspecting either the first part produced by the new process or a sample from the first batch of parts. First article inspection is typically a purchase order requirement of the purchaser for the supplier to complete. If the manufacturer doesn't have the in-house capability or if the purchaser requests, the first article inspection may be conducted by an approved subcontract supplier such as a dimensional inspection/metrology laboratory.
PTC Windchill is a family of Product Lifecycle Management (PLM) software products that is offered by PTC. In 2004, as part of their expansion in the area of collaboration tools, they arranged having "a hosted version of Windchill to small- and medium-sized customers." As of 2011, products from its marketer, PTC, were being used by over 1.1 million users worldwide.
Predictive engineering analytics (PEA) is a development approach for the manufacturing industry that helps with the design of complex products. It concerns the introduction of new software tools, the integration between those, and a refinement of simulation and testing processes to improve collaboration between analysis teams that handle different applications. This is combined with intelligent reporting and data analytics. The objective is to let simulation drive the design, to predict product behavior rather than to react on issues which may arise, and to install a process that lets design continue after product delivery.