62,002 research outputs found
Set-Based Concurrent Engineering Model for Automotive Electronic/Software Systems Development
Organised by: Cranfield UniversityThis paper is presenting a proposal of a novel approach to automotive electronic/software systems
development. It is based on the combination of Set-Based Concurrent Engineering, a Toyota approach to
product development, with the standard V-Model of software development. Automotive industry currently
faces the problem of growing complexity of electronic/software systems. This issue is especially visible at
the level of integration of these systems which is difficult and error-prone. The presented conceptual
proposal is to establish better processes that could handle the electronic/software systems design and
development in a more integrated and consistent manner.Mori Seiki – The Machine Tool Compan
Beyond the Big Leave: The Future of U.S. Automotive Human Resources
Based on industry interviews and trends analyses, forecasts employment levels and hiring nationwide and in Michigan through 2016, and compiles automakers' input on technical needs, hiring criteria, and suggestions for training and education curricula
Predicting and Evaluating Software Model Growth in the Automotive Industry
The size of a software artifact influences the software quality and impacts
the development process. In industry, when software size exceeds certain
thresholds, memory errors accumulate and development tools might not be able to
cope anymore, resulting in a lengthy program start up times, failing builds, or
memory problems at unpredictable times. Thus, foreseeing critical growth in
software modules meets a high demand in industrial practice. Predicting the
time when the size grows to the level where maintenance is needed prevents
unexpected efforts and helps to spot problematic artifacts before they become
critical.
Although the amount of prediction approaches in literature is vast, it is
unclear how well they fit with prerequisites and expectations from practice. In
this paper, we perform an industrial case study at an automotive manufacturer
to explore applicability and usability of prediction approaches in practice. In
a first step, we collect the most relevant prediction approaches from
literature, including both, approaches using statistics and machine learning.
Furthermore, we elicit expectations towards predictions from practitioners
using a survey and stakeholder workshops. At the same time, we measure software
size of 48 software artifacts by mining four years of revision history,
resulting in 4,547 data points. In the last step, we assess the applicability
of state-of-the-art prediction approaches using the collected data by
systematically analyzing how well they fulfill the practitioners' expectations.
Our main contribution is a comparison of commonly used prediction approaches
in a real world industrial setting while considering stakeholder expectations.
We show that the approaches provide significantly different results regarding
prediction accuracy and that the statistical approaches fit our data best
Boundary Objects and their Use in Agile Systems Engineering
Agile methods are increasingly introduced in automotive companies in the
attempt to become more efficient and flexible in the system development. The
adoption of agile practices influences communication between stakeholders, but
also makes companies rethink the management of artifacts and documentation like
requirements, safety compliance documents, and architecture models.
Practitioners aim to reduce irrelevant documentation, but face a lack of
guidance to determine what artifacts are needed and how they should be managed.
This paper presents artifacts, challenges, guidelines, and practices for the
continuous management of systems engineering artifacts in automotive based on a
theoretical and empirical understanding of the topic. In collaboration with 53
practitioners from six automotive companies, we conducted a design-science
study involving interviews, a questionnaire, focus groups, and practical data
analysis of a systems engineering tool. The guidelines suggest the distinction
between artifacts that are shared among different actors in a company (boundary
objects) and those that are used within a team (locally relevant artifacts). We
propose an analysis approach to identify boundary objects and three practices
to manage systems engineering artifacts in industry
Transferring Collective Knowledge: Collective and Fragmented Teaching and Learning in the Chinese Auto Industry
Collective knowledge, consisting of tacit group-embedded knowledge, is a key element of organizational capabilities. This study undertakes a multiple-case study of the transfer of collective knowledge, guided by a set of tentative constructs and propositions derived from organizational learning theory. By focusing on the group-embeddedness dimension of collective knowledge, we direct our attention to the source and recipient communities. We identify two sets of strategic choices concerning the transfer of collective knowledge: collective vs. fragmented teaching, and collective vs. fragmented learning. The empirical context of this study is international R&D capability transfer in the Chinese auto industry. From the case evidence, we find the expected benefits of collective teaching and collective learning, and also discover additional benefits of these two strategies, including the creation of a bridge network communication infrastructure. The study disclosed other conditions underlying the choice of strategies of transferring collective knowledge, including transfer effort and the level of group-embeddedness of the knowledge to be taught or re-embedded. The paper provides a group-level perspective in understanding organizational capabilities, as well as a set of refined constructs and propositions concerning strategic choices of transferring collective knowledge. The study also provides a rich description of the best practices and lessons learned in transferring organizational capabilities.http://deepblue.lib.umich.edu/bitstream/2027.42/39804/3/wp420.pd
Noise Mitigation Analysis of a Pi-Filter for an Automotive Control Module
This paper has been reproduced on " InCompliance" magazine, May issue http://www.incompliancemag.com/ then "Issue Archive
Towards a Formalism-Based Toolkit for Automotive Applications
The success of a number of projects has been shown to be significantly
improved by the use of a formalism. However, there remains an open issue: to
what extent can a development process based on a singular formal notation and
method succeed. The majority of approaches demonstrate a low level of
flexibility by attempting to use a single notation to express all of the
different aspects encountered in software development. Often, these approaches
leave a number of scalability issues open. We prefer a more eclectic approach.
In our experience, the use of a formalism-based toolkit with adequate notations
for each development phase is a viable solution. Following this principle, any
specific notation is used only where and when it is really suitable and not
necessarily over the entire software lifecycle. The approach explored in this
article is perhaps slowly emerging in practice - we hope to accelerate its
adoption. However, the major challenge is still finding the best way to
instantiate it for each specific application scenario. In this work, we
describe a development process and method for automotive applications which
consists of five phases. The process recognizes the need for having adequate
(and tailored) notations (Problem Frames, Requirements State Machine Language,
and Event-B) for each development phase as well as direct traceability between
the documents produced during each phase. This allows for a stepwise
verification/validation of the system under development. The ideas for the
formal development method have evolved over two significant case studies
carried out in the DEPLOY project
An Exploratory Study of Forces and Frictions affecting Large-Scale Model-Driven Development
In this paper, we investigate model-driven engineering, reporting on an
exploratory case-study conducted at a large automotive company. The study
consisted of interviews with 20 engineers and managers working in different
roles. We found that, in the context of a large organization, contextual forces
dominate the cognitive issues of using model-driven technology. The four forces
we identified that are likely independent of the particular abstractions chosen
as the basis of software development are the need for diffing in software
product lines, the needs for problem-specific languages and types, the need for
live modeling in exploratory activities, and the need for point-to-point
traceability between artifacts. We also identified triggers of accidental
complexity, which we refer to as points of friction introduced by languages and
tools. Examples of the friction points identified are insufficient support for
model diffing, point-to-point traceability, and model changes at runtime.Comment: To appear in proceedings of MODELS 2012, LNCS Springe
Transdisciplinarity seen through Information, Communication, Computation, (Inter-)Action and Cognition
Similar to oil that acted as a basic raw material and key driving force of
industrial society, information acts as a raw material and principal mover of
knowledge society in the knowledge production, propagation and application. New
developments in information processing and information communication
technologies allow increasingly complex and accurate descriptions,
representations and models, which are often multi-parameter, multi-perspective,
multi-level and multidimensional. This leads to the necessity of collaborative
work between different domains with corresponding specialist competences,
sciences and research traditions. We present several major transdisciplinary
unification projects for information and knowledge, which proceed on the
descriptive, logical and the level of generative mechanisms. Parallel process
of boundary crossing and transdisciplinary activity is going on in the applied
domains. Technological artifacts are becoming increasingly complex and their
design is strongly user-centered, which brings in not only the function and
various technological qualities but also other aspects including esthetic, user
experience, ethics and sustainability with social and environmental dimensions.
When integrating knowledge from a variety of fields, with contributions from
different groups of stakeholders, numerous challenges are met in establishing
common view and common course of action. In this context, information is our
environment, and informational ecology determines both epistemology and spaces
for action. We present some insights into the current state of the art of
transdisciplinary theory and practice of information studies and informatics.
We depict different facets of transdisciplinarity as we see it from our
different research fields that include information studies, computability,
human-computer interaction, multi-operating-systems environments and
philosophy.Comment: Chapter in a forthcoming book: Information Studies and the Quest for
Transdisciplinarity - Forthcoming book in World Scientific. Mark Burgin and
Wolfgang Hofkirchner, Editor
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