Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
Session Overview
Session
SES 3.4: Manufacturing Operations, Supply Chain and Logistics
Time:
Tuesday, 27/Jun/2017:
4:30pm - 5:30pm

Session Chair: Teresa Pereira
Location: Aula P (first floor)

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Presentations

237. A TCO model for supporting the investment analysis of industrial plants

Marco Mandolini, Eugenia Marilungo, Michele Germani

Università Politecnica delle Marche, Italy

In the current industrial context, where processes are extremely flexible to meet the market demand and companies pay more and more attention to satisfy the customers’ needs, the traditional cost assessment methods are too restrictive because they consider only the manufacturing phase of a product. A novel lifecycle approach that considers also the cost incurred during the product use and end of life phases is required. The Total Cost of Ownership (TCO) is the method conceived for solving this problem and it is becoming very attracting for its long term advantages in terms of cost saving. For instance, when an investment manager approaches and assesses a new investment (e.g. production machine, utility, production line, building), he needs to know the lifecycle costs of that item, in order to optimize the long-term costs. Moreover, during the investment analysis for a new asset (or revamping of an existing one) it is crucial for the investment manager knows the life cycle data for the asset of their suppliers: this is the crucial aspect of applying the TCO method for preventive analysis.

The scientific and industrial literature contains several applications of such a method. The first branch of research applies the TCO method during the procurement phase of a product/service as a support for the supplier selection. The main limitation of such approaches is that they are not integrated with the design phase of a product nor they are applied for the industrial assets. The TCO method is also used for the consumptive analysis of a product/process, once it is running at the facility of the owner, for evaluating future scenario such as revamping or substitution. The use of the TCO method for the preventive analysis is not well investigated.

The paper presents a TCO model for the preventive analysis of industrial assets, which can be used during the design phase, for supporting the asset configuration, and during the procurement phase, for supporting the supplier selection and negotiation. At the design phase, the model foresees a configuration framework, which allows the designer to configure the asset by selecting its feature in accordance to the product to realize. The model inform the designer about the preventive TCO of each possible solution (a solution consists of a combination of supplier and asset technology). At the procurement phase, the model allows the investment manager to select the best supplying strategy by simulating and optimizing different scenarios. A scenario consists of an asset technology, supplier, production plant and useful asset life.

To foster the TCO model application, the authors developed a preliminary software application distributed to designers and investment managers. The model and relative software tool is under test by an Italian company of the agribusiness sector, which aims to optimize the design and procurement phase of their assets.


243. Applications’ Integration and Operation Platform to Support Smart Manufacturing for Small and Medium-sized Enterprises

Chanmo Jun1, Ju Yeon Lee1, Joo-Sung Yoon2, Bo Hyun Kim1

1KITECH, Korea, Republic of (South Korea); 2Smart Manufacturing Technology Group, Korea Institute of Industrial Technology, 89, Yangdaegiro-gil, Giro-ri, Ipjang-myeon, Seobuk-gu, Cheonan-si, Chungcheongnam-do, 31056, South Korea

Many developed countries are making various efforts to innovate their own manufacturing industries, through initiatives such as Manufacturing innovation 3.0, Industry 4.0, and Manufacturing 2025. Innovation in the manufacturing industry, represented by the so-called “smart factories,” is being developed through the latest technologies such as Internet of Things (IoT), Cloud, and Big data. However, as the application of these technologies requires a lot of cost and time, small and medium-sized enterprises are often hampered in their efforts to take full advantage of them. For an enterprise that operates a manufacturing information system, the integrated management of information between systems is essential to the application of a new technology. If the enterprise lacks the relevant experts, it will have difficulty applying a new technology in the field. This study suggests the application of a cloud-based Applications’ Integration and Operation Platform in order to resolve those problems. The Applications’ Integration and Operation Platform must accept a large volume of data at IoT-based manufacturing fields, interconnect between manufacturing fields and Applications’ Integration and Operation Platform, and provide application contents in the form of service. The suggested study contents are applied to a company that produces plastic injection models to verify their effects. It is expected that this study can be used as a reference model for applying smart factory technologies to other small and medium-sized enterprises in the future.


80. Organizational Performance and Indicators: Trends and Opportunities

Fernanda Antunes Silva, Milton Borsato

UTFPR, Brazil

Given the current competition into markets, it’s necessary for companies to monitor their practices and results in order to ensure competitiveness. To survive these challenges and compete successfully, organizations need to monitor processes through key performance indicators (KPIs). Currently, indicators are analyzed in an isolated way within the organizations. Therefore, it’s important that companies use a harmonization approach both in the creation and monitoring process of indicators. Based on it, this article carries out a research to find the state of the art and the research opportunities. To do that, a bibliographic portfolio was constructed and bibliometric and systemic analyzes were performed.



 
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