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Scope Management
Published in Adedeji B. Badiru, Abidemi S. Badiru, Adetokunboh I. Badiru, Mechanics of Project Management, 2018
Adedeji B. Badiru, Abidemi S. Badiru, Adetokunboh I. Badiru
The primary purpose of project scope definition is to explore deeper details of stakeholder needs, wants, desires, and expectations for the purpose of creating project requirements. It requires an outline of additional constraints and assumptions for implementing the project. Product analysis develops a better understanding of the product of the project. Stakeholder analysis identifies the influence and interests of stakeholders and documents their needs in order to create project requirements. In addition, project scope definition provides a documented basis for making future project decisions and it covers the following: Justification: Why is the project needed?Product description: What is the expected product of the project?Boundaries: What is included and not included in the project?Constraints and AssumptionsDeliverables: What are the project deliverables?Objectives: How will the success of the project be assessed?
Data and model-based triple V product development framework and methodology
Published in Enterprise Information Systems, 2022
Qing Li, Hailong Wei, Chao Yu, Shuangshuang Wang
Harmony is a MBSE method proposed by IBM, usually realised upon the supporting tool Rational Rhapsody (Mazeika, Morkevicius, and Aleksandraviciene (2016)). Harmony coordinates a request-driven approach with SysML and UML, including two loosely coupled parts: Harmony for Systems Engineering and Harmony for Embedded Real Time Development (Morkevicius et al. (2020)). Figure 5 maps the IBM Harmony to the double V framework. In Harmony methodology, V model includes requirement analysis, functional analysis, design synthesis, product analysis and design, product implementation and corresponding unit test, module integration and test, (subsystem integration and test), system acceptance test. Stakeholder’s requirements as input will go through the design specification to integration, and the input and output of each stage are presented in the form of models. Moreover, the evolution of the system is carried out in an iterative way, and the change of the system will trigger a new iterative cycle.
A model-based systems engineering approach for developing modular system architectures
Published in Journal of Engineering Design, 2022
Benjamin W. Stirgwolt, Thomas A. Mazzuchi, Shahram Sarkani
In contrast to the architecting processes described in the systems engineering literature, in the product development literature there is an emphasis on defining modules as a fundamental component of the architecting process. Ulrich and Eppinger (2011) suggest that modularity is the most important characteristic of a product architecture. Otto et al. (2016) reviewed the product design literature and identified the common process steps in the early stages of product design. Many of the same processes steps that are included in the Vee process and the model-based system architecting processes also appear in their sequence of architecting steps. However, they suggest that as part of the product development process, before an architecture is down selected, it is partitioned into modules. Likewise, Kamrani and Salhieh (2002) describe a process for developing a system, starting with a needs and requirements analysis, performing a decomposition analysis (functional, structural, and function-mapping into elements), conducting a product analysis (design for assembly), as well as a process analysis (design for manufacture). An integral part of their process is the grouping of elements into modules. In the product design literature, there is a consistent focus on the determination of modules as described by Jiao, Simpson, and Siddique (2007), AlGeddawy and ElMaraghy (2013), and Bonvoisin et al. (2016), which is absent from the systems engineering literature.
A critical investigation of Industry 4.0 in manufacturing: theoretical operationalisation framework
Published in Production Planning & Control, 2018
Hajar Fatorachian, Hadi Kazemi
The need for effective management and coordination of resources for better production planning in manufacturing industry has resulted in creation of information systems (Koh and Saad 2006). However, based on Koh, Gunasekaran, and Rajkumar (2008), currently available information systems such as Enterprise Resources Planning (ERP) systems, Advanced Planning and Scheduling (APS), and Supply Chain Management (SCM) do not fully address the collaboration and integration challenges in manufacturing operations. In order to ensure complete connectivity within an enterprise, intelligent software systems should be established to enable regular communication with intelligent devices, machinery and processes (Brousell, Moad, and Tate 2014). For example, management software systems such as Product Lifecycle Management (PLM) which capture all information related to products throughout the value chain, enable real-time communication and realisation of ‘single source of truth’ across the complete product life cycle (Gecevska et al. 2012; Schuh et al. 2014). This capability can have a significant impact on product analysis, design and development.