Antipasti

2019 ◽  
pp. 108-130
Keyword(s):  
Process Modeling ◽  
Design Thinking ◽  
Enterprise Modeling ◽  
Working Environment ◽  
Organizational Models ◽  
Modeling Framework ◽  
Business Environments ◽  
Hands On ◽  
Agile Enterprise ◽  
Tools And Techniques

Nowadays megatrend of Industry 4.0 initiative in complex and dynamic business environments require easy and hands-on methods for enterprise modelling that will be able to recalibrate process's models constantly. Processes are often declared as being “modeled” or “documented” but seldom as being “designed.” This leads to certain afflictions in allocation of the particular resources required for the tasks of process modeling or design. There is perception of process modeling as a routine task, which is structured itself by “modeling terms and conditions” or “modeling agreement,” while “design thinking” is mainly considered as much more less structured and belonging to the artist's nature. Implementation of such models in practice or IT automation does not fit the reality because of misinterpretation from the start of modeling and multiplied on each step of model transformation. In such circumstances any thought about fruitful digitalization looks very abused. This chapter describes a set of tools and techniques for enriching organizational models with semantic information and adjusting them on request. Firstly, this chapter considers an innovative approach for the model binding with relevant documents and experts. Secondly, factors that trigger models' changes using company's information environment (field) are defined. Thirdly, an agile enterprise-modeling framework that automatically adapts to the business situation, creating context-aware working environment for employees, is introduced.

scholarly journals Conformance Analysis of Organizational Models

2013 ◽  
Vol 4 (1) ◽  
pp. 42-78 ◽  
Author(s):  
Christoph Brandt ◽  
Frank Hermann
Keyword(s):  
Coming Out ◽  
Enterprise Modeling ◽  
Security Risk ◽  
Organizational Models ◽  
Modeling Framework ◽  
Holistic Model ◽  
New Approach ◽  
Finance Industry ◽  
Partial Models ◽  
Compliance Constraints

Organizational models play a key role in today’s enterprise modeling. They usually show up as partial models produced in a distributed and non-synchronized fashion by people with different conceptual understandings. For this reason, there is a major need to organize partial organizational models within a suitable modeling framework, and, moreover, to check their mutual conformance. This builds the basis to integrate the partial organizational models later on into one holistic model of the organization and for model checking certain security, risk, and compliance constraints. In order to attain this goal, the authors present two mutually aligned contributions. The first one is a new enterprise modeling framework—the EM-Cube. The second one is a new approach for checking conformance of models based on the suggested formal modeling technique associated with the proposed framework. They evaluate the potential solution against concrete requirements derived from a real-world scenario coming out of the finance industry.

Hands on Design Thinking

2019 ◽  
Author(s):  
Conrad Glitza ◽  
Rosa-Sophie Hamburger ◽  
Michael Metzger
Keyword(s):  
Design Thinking ◽  
Hands On

Why Is Safe Science Good Science?

2018 ◽  
Author(s):  
Camilla Kao ◽  
Che-I Kao ◽  
Russell Furr
Keyword(s):  
Decision Making ◽  
Design Thinking ◽  
Good Science ◽  
Safety Issues ◽  
Safety Requirements ◽  
The Arts ◽  
Hands On ◽  
Obvious Benefit ◽  
New Ideas

In science, safety can seem unfashionable. Satisfying safety requirements can slow the pace of research, make it cumbersome, or cost significant amounts of money. The logic of rules can seem unclear. Compliance can feel like a negative incentive. So besides the obvious benefit that safety keeps one safe, why do some scientists preach "safe science is good science"? Understanding the principles that underlie this maxim might help to create a strong positive incentive to incorporate safety into the pursuit of groundbreaking science.<div><br></div><div>This essay explains how safety can enhance the quality of an experiment and promote innovation in one's research. Being safe induces a researcher to have <b>greater control</b> over an experiment, which reduces the <b>uncertainty</b> that characterizes the experiment. Less uncertainty increases both <b>safety</b> and the <b>quality</b> of the experiment, the latter including <b>statistical quality</b> (reproducibility, sensitivity, etc.) and <b>countless other properties</b> (yield, purity, cost, etc.). Like prototyping in design thinking and working under the constraint of creative limitation in the arts, <b>considering safety issues</b> is a hands-on activity that involves <b>decision-making</b>. Making decisions leads to new ideas, which spawns <b>innovation</b>.</div>

scholarly journals Use of scenario development and personal learning environment and networks (PLE&N) to support curriculum co-creation

2018 ◽  
Vol 13 (2) ◽  
pp. 848-858 ◽  
Author(s):  
Eric Tsui ◽  
Nikolina Dragicevic
Keyword(s):  
Learning Environment ◽  
Learning Outcomes ◽  
Design Methodology ◽  
Working Environment ◽  
Scenario Development ◽  
Learning Space ◽  
Personal Learning ◽  
Personal Learning Environment ◽  
Business Environments ◽  
Constant Change

AbstractIn much of the current discussions on business environments, a recurring theme both for academics and practitioners is that it is marked by inherent uncertainty (unknown unknowns). Hence, knowledge workers must have skills and understanding of the possible ways to navigate through and adapt to constant change. However, the tendency of prevailing approaches to curriculum development to focus on (static) learning outcomes, we argue, is not appropriate to train young people to adapt to the unpredictable working environment. Instead, more dynamic approaches to curriculum are required, which would instead focus on learning as a continuous relearning and emergent process of adaptation and stimulate students' inquiry and intellectual and creative skills. This paper approaches the issue by discussing the opportunities of using scenario thinking and development together with a personal learning environment and network (PLE&N) for co-creating a curriculum with students, teachers, and practitioners in higher education. In short, the methodology underpinning scenario development recognizes that uncertainty can be best dealt with and understood from the perspective of a range of possibilities and multiple futures through a facilitated, coherently structured process. PLE&N, on the other hand, serves as a learning space which stimulates self-regulated and network-based learning. The paper contends that curriculum informed by such a design methodology would lead to more frequent and appropriate updates as well as equip students with skills to work in a volatile, uncertain, complex, and ambiguous (VUCA) environment.

scholarly journals DESIGN THINKING: CONCEPTUAL FRAMEWORK, ADVANTAGES AND RESTRICTIONS

2021 ◽  
pp. 43-48
Author(s):  
Sytnik N.
Keyword(s):  
Corporate Culture ◽  
Design Thinking ◽  
Team Building ◽  
Deep Understanding ◽  
Customer Experience ◽  
Organizational Goals ◽  
Innovative Products ◽  
Creative Abilities ◽  
Stanford Model ◽  
Tools And Techniques

The need to develop competitive innovative products and services encourages modern organizations to search for new ways to enhance the creative abilities of their personnel. Design thinking is one of the promising tools to elaborate organi-zational potential in generating ideas and developing new products which satisfy customer requirements to the most extent. Over last years design thinking has been developed as a practically­oriented approach aimed at solving customer problems. Within the frame of design thinking, deep understanding of their values, reactions, experience in interaction with the company and behavioral habits serves as a basis for focused ideation, fast prototyping and testing. Although the key characteristics, main stages, tools and techniques of design thinking are well established in the literature, far less attention has been paid to the restrictions and conditions of design thinking application within organizational environment. These issues determined the purpose of the study. First, the paper considered the evolution of the term design thinking, as well as portfolio of its tools and techniques applied at different stages of design thinking process. Further, the advantages, restrictions and conditions of design thinking application were specified. Design thinking allows to achieve 1) externally oriented organizational goals: development of innovations, improvement of products and services in accordance with customer needs, better interaction with customers; 2) internally oriented organizational goals: development of staff experience and creative abilities, team building and enchancing a creative corporate culture. The restrictions of design thinking implementation related to its key features (focus on customer experience, fast ideation, prototyping and testing) were established. Important conditions for design thinking implementation are as follows: understanding and taking into account its restrictions, introduction of a flexible format for design sessions, and formation of design teams in accordance with the experience, competencies and thinking style of their participants. Thus, design thinking is a useful approach for development of customer­oriented innovative solutions, although it should not be considered as a universal tool for solving all organizational problems.Keywords: design, design thinking, creativity, customer experience, Stanford model, «wicked» problems, design thinking techniques. Дизайн­мислення є перспективним напрямом дослідження для науковців і фахівців із менеджменту, ураховуючи позитивний досвід його використання і зростаючу популярність серед провідних компаній світу. Нині відомі характерні риси, етапи, інструменти та техніки дизайн­мислення, однак малодослідженим залишається питання щодо меж практичного застосування цього підходу, його переваг і недоліків. У статті виявлено переваги дизайн­мислення, зокрема: оперативне вдосконалення продуктів і послуг відповідно до потреб клієнтів, тімбілдинг, новий досвід і розвиток креативних здібностей персоналу, формування креативної корпоративної культури. Для успішного застосування дизайн­мислення під час організації дизайн­сесій необхідно враховувати його обмеження, упроваджувати гнучкий формат дизайн­сесій та підбирати учасників дизайн­команд за досвідом, компетенціями і стилем мислення. Ключові слова: дизайн, дизайн­мислення, креативність, клієнтський досвід, Стенфордська модель, wicked­проблеми, техніки дизайн­мислення.

EFFECT OF BOUNDARY CONDITIONS ON PROCESS- INDUCED STRESSES IN A PLAIN WEAVE UNIT CELL

2021 ◽  
Author(s):  
K. BUKENYA ◽  
M. N. OLAYA ◽  
E. J. PINEDA ◽  
M. MAIARU
Keyword(s):  
Finite Element ◽  
Boundary Conditions ◽  
Process Modeling ◽  
Complex Geometry ◽  
Polymer Matrix Composites ◽  
Unit Cell ◽  
Modeling Framework ◽  
Element Analysis ◽  
Finite Element Software ◽  
Aerospace Applications

Woven polymer matrix composites (PMCs) are leveraged in aerospace applications for their desirable specific properties, yet they are vulnerable to high residual stresses during manufacturing and their complex geometry makes experimental results difficult to observe. Process modeling is needed to characterize the effects of the curing and predict end stress states. Finite element software can be used to model woven architectures, however accurate representation of processing conditions remains a challenge when it comes to selecting boundary conditions. The effect of BCs on process-induced stress within woven PMCs is studied. The commercial Finite Element Analysis (FEA) software Abaqus is coupled with user-written subroutines in a process modeling framework. A two-dimensionally (2D) woven PMC repeating unit cell (RUC) is modeled with TexGen and Abaqus. Virtual curing is imposed on the bulk matrix. The BC study is conducted with Free, Periodic, Flat, and Flat-Free configurations. Results show that the end stress state is sensitive to the boundary condition assumptions. Flat BC results show great agreement with Periodic BCs. Residual stress results from process modeling are then compared with a linear-elastic thermal cooldown analysis in Abaqus. Cooldown results indicate an overestimation in matrix stresses compared with process modeling.

An Ontology-Driven Process Modeling Framework

2004 ◽  
pp. 13-23 ◽  
Author(s):  
Gianluigi Greco ◽  
Antonella Guzzo ◽  
Luigi Pontieri ◽  
Domenico Saccà
Keyword(s):  
Process Modeling ◽  
Modeling Framework

scholarly journals A practical guide to mechanistic systems modeling in biology using a logic-based approach

2020 ◽  
Author(s):  
Anna Niarakis ◽  
Tomáš Helikar
Keyword(s):  
Computational Modeling ◽  
Computational Models ◽  
Regulatory System ◽  
Mechanistic Modeling ◽  
Lac Operon ◽  
Modeling Framework ◽  
Validation Criteria ◽  
Hands On ◽  
Modeling Software ◽  
Logical Modeling

Abstract Mechanistic computational models enable the study of regulatory mechanisms implicated in various biological processes. These models provide a means to analyze the dynamics of the systems they describe, and to study and interrogate their properties, and provide insights about the emerging behavior of the system in the presence of single or combined perturbations. Aimed at those who are new to computational modeling, we present here a practical hands-on protocol breaking down the process of mechanistic modeling of biological systems in a succession of precise steps. The protocol provides a framework that includes defining the model scope, choosing validation criteria, selecting the appropriate modeling approach, constructing a model and simulating the model. To ensure broad accessibility of the protocol, we use a logical modeling framework, which presents a lower mathematical barrier of entry, and two easy-to-use and popular modeling software tools: Cell Collective and GINsim. The complete modeling workflow is applied to a well-studied and familiar biological process—the lac operon regulatory system. The protocol can be completed by users with little to no prior computational modeling experience approximately within 3 h.

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