scholarly journals Robust Optimization Model for R&D Project Selection under Uncertainty in the Automobile Industry

2020 ◽  
Vol 12 (23) ◽  
pp. 10210
Author(s):  
Seunghoon Lee ◽  
Yongju Cho ◽  
Minjae Ko
Keyword(s):  
Robust Optimization ◽  
Automobile Industry ◽  
New Technologies ◽  
Project Selection ◽  
Decision Makers ◽  
Cost Uncertainty ◽  
Proposed Model ◽  
Key Factor ◽  
Long Time ◽  
A Company

In a company, project management is responsible for project selection from candidates under some limited constraints to achieve the company’s goal before the project begins as well as the project operations in progress. The development of new technologies and products can broaden a company’s market share, and to do so, research and development (R&D) projects are significant. However, limited funds force a company to select projects that can best represent the company’s interests. As projects may take a long time to develop, a number of uncertainties may occur, and the most concerning uncertainty is cost uncertainty. In this study, a robust optimization decision model for project selection considering cost uncertainty is proposed to assist the decision-making process for companies that need to select projects from a number of candidates due to limited funds. The model considers project selection in view of the total cost of ownership, which is a key factor for customers and companies in the automobile industry. The proposed model is tested in the automobile industry environment with different conservatism levels about cost uncertainty, and an analysis of expected market changes and a company’s income is performed with the solutions obtained from the proposed model. The result shows that the presented model reacts to cost uncertainty robustly for assisting the decision-makers in the company.

scholarly journals Impact of Industry 4.0 on decision-making in an operational context

2021 ◽  
Vol 16 (4) ◽  
pp. 500-514
Author(s):  
F. Rosin ◽  
P. Forget ◽  
S. Lamouri ◽  
R. Pellerin
Keyword(s):  
Decision Making ◽  
Industry 4.0 ◽  
New Technologies ◽  
Production Systems ◽  
Point Of View ◽  
Decision Makers ◽  
Process Improvements ◽  
Proposed Model ◽  
Operational Systems ◽  
Decision Making Processes

The implementation of Industry 4.0 technologies suggests significant impacts on production systems productivity and decision-making process improvements. However, many manufacturers have difficulty determining to what extent these various technologies can reinforce the autonomy of teams and operational systems. This article addresses this issue by proposing a model describing different types of autonomy and the contribution of 4.0 technologies in the various steps of the decision-making processes. The model was confronted with a set of application cases from the literature. It emerges that new technologies' improvements are significant from a decision-making point of view and may eventually favor implementing new modes of autonomy. Decision-makers can rely on the proposed model to better understand the opportunities linked to the fusion of cybernetic, physical, and social spaces made possible by Industry 4.0.

Decision making based on intuitionistic fuzzy preference relations with additive approximate consistency

2020 ◽  
Vol 39 (3) ◽  
pp. 4041-4058
Author(s):  
Fang Liu ◽  
Xu Tan ◽  
Hui Yang ◽  
Hui Zhao
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Real Interval ◽  
Preference Relations ◽  
Intuitionistic Fuzzy ◽  
Proposed Model ◽  
Fuzzy Preference Relations ◽  
Novel Concept ◽  
Fuzzy Weights ◽  
Fuzzy Preference

Intuitionistic fuzzy preference relations (IFPRs) have the natural ability to reflect the positive, the negative and the non-determinative judgements of decision makers. A decision making model is proposed by considering the inherent property of IFPRs in this study, where the main novelty comes with the introduction of the concept of additive approximate consistency. First, the consistency definitions of IFPRs are reviewed and the underlying ideas are analyzed. Second, by considering the allocation of the non-determinacy degree of decision makers’ opinions, the novel concept of approximate consistency for IFPRs is proposed. Then the additive approximate consistency of IFPRs is defined and the properties are studied. Third, the priorities of alternatives are derived from IFPRs with additive approximate consistency by considering the effects of the permutations of alternatives and the allocation of the non-determinacy degree. The rankings of alternatives based on real, interval and intuitionistic fuzzy weights are investigated, respectively. Finally, some comparisons are reported by carrying out numerical examples to show the novelty and advantage of the proposed model. It is found that the proposed model can offer various decision schemes due to the allocation of the non-determinacy degree of IFPRs.

Examining the significance of market research in the case of start-ups

2014 ◽  
Vol 5 (2) ◽  
pp. 181-190
Author(s):  
A. Matkó ◽  
E. Szűcs ◽  
T. Takács ◽  
S. Kovács
Keyword(s):  
Research Methods ◽  
Market Research ◽  
New Technologies ◽  
Start Ups ◽  
A Company

Today, companies have to face new challanges because of the globalization, new technologies, globalization of markets and increasing competition. In this accelerated world, it is essential that the companies adapt to the market, which is only available through the necessary information. The importance of market research is undoubted. In our study we would like to prove that in case of a beginner company — in this case a confectionery — it is important to perform a market research like for a company in any other segment. To perform it, the qualitative market research methods were used. Our questionnaire examines several aspects in order to provide an indication of the company’s founding.

IDLE WELLS REHABILITATION IN THE FIELDS OF EXTREME NORTH

2015 ◽  
pp. 66-71
Author(s):  
A. V. Kustyshev
Keyword(s):  
New Technologies ◽  
Long Time ◽  
Extreme North

The paper reviews the new technologies developed for rehabilitation of wells being out of operating for a long time. It presents a complex of works needed for such wells brining back into operation

Risk-Based Robust Bidding Strategies for EVs’ Aggregators in Day-ahead Markets with Uncertainty

2020 ◽  
Author(s):  
Ahmed Abdelmoaty ◽  
Wessam Mesbah ◽  
Mohammad A. M. Abdel-Aal ◽  
Ali T. Alawami
Keyword(s):  
Robust Optimization ◽  
Electricity Market ◽  
Real Life ◽  
Optimization Approach ◽  
Case Scenario ◽  
Worst Case ◽  
Bidding Strategies ◽  
Wind Generators ◽  
Proposed Model ◽  
Optimal Bidding

In the recent electricity market framework, the profit of the generation companies depends on the decision of the operator on the schedule of its units, the energy price, and the optimal bidding strategies. Due to the expanded integration of uncertain renewable generators which is highly intermittent such as wind plants, the coordination with other facilities to mitigate the risks of imbalances is mandatory. Accordingly, coordination of wind generators with the evolutionary Electric Vehicles (EVs) is expected to boost the performance of the grid. In this paper, we propose a robust optimization approach for the coordination between the wind-thermal generators and the EVs in a virtual<br>power plant (VPP) environment. The objective of maximizing the profit of the VPP Operator (VPPO) is studied. The optimal bidding strategy of the VPPO in the day-ahead market under uncertainties of wind power, energy<br>prices, imbalance prices, and demand is obtained for the worst case scenario. A case study is conducted to assess the e?effectiveness of the proposed model in terms of the VPPO's profit. A comparison between the proposed model and the scenario-based optimization was introduced. Our results confirmed that, although the conservative behavior of the worst-case robust optimization model, it helps the decision maker from the fluctuations of the uncertain parameters involved in the production and bidding processes. In addition, robust optimization is a more tractable problem and does not suffer from<br>the high computation burden associated with scenario-based stochastic programming. This makes it more practical for real-life scenarios.<br>

scholarly journals Optimizing a Reverse Supply Chain Network for Electronic Waste under Risk and Uncertain Factors

2021 ◽  
Vol 11 (4) ◽  
pp. 1946
Author(s):  
Linh Thi Truc Doan ◽  
Yousef Amer ◽  
Sang-Heon Lee ◽  
Phan Nguyen Ky Phuc ◽  
Tham Thi Tran
Keyword(s):  
Supply Chain ◽  
Electronic Waste ◽  
Decision Makers ◽  
Reverse Supply Chain ◽  
Satisfactory Solution ◽  
Level Of Satisfaction ◽  
Proposed Model ◽  
Objective Value ◽  
The Right ◽  
The Impact

Minimizing the impact of electronic waste (e-waste) on the environment through designing an effective reverse supply chain (RSC) is attracting the attention of both industry and academia. To obtain this goal, this study strives to develop an e-waste RSC model where the input parameters are fuzzy and risk factors are considered. The problem is then solved through crisp transformation and decision-makers are given the right to choose solutions based on their satisfaction. The result shows that the proposed model provides a practical and satisfactory solution to compromise between the level of satisfaction of constraints and the objective value. This solution includes strategic and operational decisions such as the optimal locations of facilities (i.e., disassembly, repairing, recycling facilities) and the flow quantities in the RSC.

scholarly journals From automobile capitalism to platform capitalism: Toyotism as a prehistory of digital platforms

2021 ◽  
pp. 017084062110306
Author(s):  
Marc Steinberg
Keyword(s):  
Automobile Industry ◽  
New Technologies ◽  
Digital Platforms ◽  
New Era ◽  
Data Intensive ◽  
New Organizational Forms ◽  
Production Practice ◽  
Industry Applications ◽  
Digital Artefact ◽  
The Relationship

This article explores the automotive lineage and manufacturing origins of platforms. Challenging prevailing assumptions that the platform is a digital artefact, and platform capitalism a new era, this article traces crucial elements of platform capitalism to Toyotist automobile manufacture in order to rethink the relationship between technology and organization. Arguing that the very terminology and industry applications of the ‘platform’ emerge from the automobile industry over the course of the 20th century, this article cautions against the uncritical adoption of epochal paradigms, or assumptions that new technologies require new organizational forms. By parsing the platform into two types, the stack and the intermediary, this article demonstrates how the platform concept and data-driven production practice both develop out of the Toyota Production System in particular, and American and Japanese analyses of it. Toyotism, we show, is the unseen industrial and epistemological background against which the platform economy plays out. In making this case, this article highlights the crucial continuities between the data intensive production of companies like Uber and Amazon – emblematic of digital platform capitalism – and the organizational paradigms of the automobile industry. At a moment when the automobile returns to prominence amidst platforms such as Uber, Didi Chuxing, or Waymo, and as we find tech companies turning to automobile manufacturing, this automotive lineage of the platform offers a crucial reminder of the automotive origins of what we now call platform capitalism.

scholarly journals Applying the Heuristic to the Risk Assessment within the Automotive Industry Supply Chain

2017 ◽  
Vol 7 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Daniela Marasova ◽  
Miriam Andrejiova ◽  
Anna Grincova
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Automobile Industry ◽  
Risk Identification ◽  
Strategic Decision ◽  
Strategic Factor ◽  
Identification Evaluation ◽  
Key Factor ◽  
The Subject ◽  
Prospective Risk

AbstractRisk management facilitates risk identification, evaluation, control, and by means of appropriate set of measures, risk reduction or complete elimination. Therefore, the risk management becomes a strategic factor for a company’s success. Properly implemented risk management system does not represent a tool to avoid the risk; it is used to understand the risk and provide the bases for strategic decision-making.Risk management represents a key factor for the supply chain operations. Managing the risks is crucial for achieving the customer satisfaction and thus also a company’s success. The subject-matter of the article is the assessment of the supply chain in the automobile industry, in terms of risks. The topicality of this problem is even higher, as after the economic crisis it is necessary to revaluate the readiness of the supply chain for prospective risk conditions. One advantage of this article is the use of the Saaty method as a tool for the risk management within the supply chain.

scholarly journals Company Changing Status and Its Linking to Competitiveness

2015 ◽  
Vol 53 (1) ◽  
pp. 1-17
Author(s):  
Dragana Radenković-Jocić ◽  
Ivan Barun
Keyword(s):  
Mergers And Acquisitions ◽  
Legal Framework ◽  
Decision Makers ◽  
Economic Activities ◽  
Economic Interests ◽  
Eu Legislation ◽  
The Republic ◽  
The Right ◽  
A Company ◽  
The Eu

Abstract The authors present the issues and challenges related to the changes in status of a company and its impact on competitiveness. Status changes of companies, mostly mergers and acquisitions of companies, are one of the ways in which capital owners and management direct economic activities with the aim of maximizing profits. In order to make the right and justified decision, in terms of achieving the economic interests of the company, it is essential to know the laws and regulations in this area. This paper should provide answers on various questions which will be presented to decision makers in every company, considering status changes. Bearing in mind that the question of status changes often associated with an international element, the authors will pay special attention on the EU legislation and current legal framework in the Republic of Serbia.

scholarly journals Ceramic Cracks Segmentation with Deep Learning

2021 ◽  
Vol 11 (13) ◽  
pp. 6017
Author(s):  
Gerivan Santos Junior ◽  
Janderson Ferreira ◽  
Cristian Millán-Arias ◽  
Ramiro Daniel ◽  
Alberto Casado Junior ◽  
...  
Keyword(s):  
Deep Learning ◽  
Ceramic Plate ◽  
Ceramic Tiles ◽  
Entire Area ◽  
Manual Inspection ◽  
Optical Inspection ◽  
Proposed Model ◽  
Processing Step ◽  
Long Time ◽  
Automated Optical Inspection

Cracks are pathologies whose appearance in ceramic tiles can cause various damages due to the coating system losing water tightness and impermeability functions. Besides, the detachment of a ceramic plate, exposing the building structure, can still reach people who move around the building. Manual inspection is the most common method for addressing this problem. However, it depends on the knowledge and experience of those who perform the analysis and demands a long time and a high cost to map the entire area. This work focuses on automated optical inspection to find faults in ceramic tiles performing the segmentation of cracks in ceramic images using deep learning to segment these defects. We propose an architecture for segmenting cracks in facades with Deep Learning that includes an image pre-processing step. We also propose the Ceramic Crack Database, a set of images to segment defects in ceramic tiles. The proposed model can adequately identify the crack even when it is close to or within the grout.

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