Program structure and sequence plans · Program structure and sequence plans BN-13133 Master of...
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Ricardo Aurélio Quinhões Pinto, Ubiratã Tortato, Claudimar Pereira da Veiga, Anderson Catapan. RAD Vol.15, n.1, Jan/Fev/Mar/Abr 2013, p.111-138. Revista Administração em Diálogo ISSN 2178-0080 Programa de Estudos Pós-Graduados em Administração Pontifícia Universidade Católica de São Paulo Página111 Gestão de estoque e lean manufacturing: estudo de caso em uma empresa metalúrgica Inventory management and lean manufacturing: a case study in a metallurgical company Ricardo Aurélio Quinhões Pinto 1 Ubiratã Tortato 2 Claudimar Pereira da Veiga 3 Anderson Catapan 4 Resumo Esta pesquisa tem como objetivo analisar o impacto da filosofia lean aplicada à gestão de estoque como diferencial de desempenho e vantagem competitiva em uma empresa metalúrgica. Trata-se de um estudo de caso descritivo, ex-post facto e de corte temporal seccional. Este estudo demonstra que após a implementação da filosofia lean, a empresa obteve maior interatividade na administração da informação entre os elementos internos e externos, o que permitiu a redução dos custos de produção, melhorias na qualidade dos produtos e eliminação dos grandes estoques de segurança sem comprometimento do nível de serviço oferecido ao cliente. Palavras-chave: Lean Manufacturing; Gestão de estoque; Empresa Metalúrgica. Abstract This research aims to analyze the impact of the lean philosophy applied to inventory management as differential performance and competitive advantage in a metallurgical company. This is a descriptive case study, ex-post facto and sectional time. This study shows that after the implementation of lean philosophy, the company achieved an information management with greater interactivity between the internal and external elements, allowing the reduction of production costs, improved product quality and the elimination of large safety stocks without compromising the level of service offered to the customer. Keyword: Lean Manufacturing, Inventory management, Metallurgical Company. 1 [email protected], Brasil. Professor da Universidade Federal de Santa Catarina – UFSC. Doutorando em Engenharia Naval e Oceânica na Universidade de São Paulo – USP. Rua Presidente Prudente de Moraes, 406, Santo Antônio, CEP: 89218-000 - Joinville, SC - Brasil. 2 [email protected]. Professora Titular da Pontifícia Universidade Católica do Paraná – PUC-PR. Doutor em Engenharia pela Universidade de São Paulo – USP. Rua Imaculada Conceição, 1155, Prado Velho, 80215901 - Curitiba, PR - Brasil 3 [email protected], Brasil. Professor da Pontifícia Universidade Católica do Paraná – PUC-PR. Doutorando em Administração na Pontifícia Universidade Católica do Paraná – PUC-PR. Rua Imaculada Conceição, 1155, Prado Velho, 80215901 - Curitiba, PR - Brasil 4 [email protected], Brasil. Professor da Pontifícia Universidade Católica do Paraná – PUC-PR. Doutorando em Administração na Pontifícia Universidade Católica do Paraná – PUC-PR. Rua Imaculada Conceição, 1155, Prado Velho, 80215901 - Curitiba, PR - Brasil Recebido em 13.10.2012 Aprovado em 28.02.2013
Transcript of Program structure and sequence plans · Program structure and sequence plans BN-13133 Master of...
Program structure and sequence plans
BN-13133 Master of Business Data Analytics (Professional)
Version 1 Jan Intake2020 DTSC71-100 DTSC71-200 STAT71-112
January Semester 1Business Analytics Coding Data Science Quantitative Methods
2020 DTSC71-301 Analytic option Business option
May Semester 2Machine Learning in Business Choose a subject from the Analytic
option
Choose a subject from the Business
option
2020 ECON71-200 DTSC71-302 Analytic option
September Semester 3Econometrics Statistical Learning and Regression
Models
Choose a subject from the Analytic
option
Subject Catalogue Major Catalogue Program Catalogue
2021 Alt. DTSCP Analytic option Business option
January Semester 1Choose either DTSC71-303 or DTSC71-
304
Choose a subject from the Analytic
option
Choose a subject from the Business
option
2021 Alt. PROF
May Semester 2Choose either BUSN71-701 OR
BUSN71-705
BN-13133 Master of Business Data Analytics (Professional)
Version 1 Sep Intake2020 DTSC71-100 DTSC71-200 STAT71-112
September Semester 1Business Analytics Coding Data Science Quantitative Methods
2021 ECON71-200 Business option Business option
January Semester 2Econometrics Choose a subject from the Business
option
Choose a subject from the Business
option
2021 DTSC71-301 DTSC71-302 Analytic option
May Semester 3Machine Learning in Business Statistical Learning and Regression
Models
Choose a subject from the Analytic
option
Subject Catalogue Major Catalogue Program Catalogue
2021 Alt. DTSCP Analytic option Analytic option
September Semester 1Choose either DTSC71-303 or DTSC71-
304
Choose a subject from the Analytic
option
Choose a subject from the Analytic
option
2022 Alt. PROF
January Semester 2Choose either BUSN71-701 OR
BUSN71-705
GENERAL INFORMATIONData Analytics has become one of the highest growth areas of academic and commercial practice. With applications in nearly all aspects of quantitative endeavours and information
management, a skillset in analytics, statistical and machine learning is highly valued and sought after. The Master of Business Data Analytics (Professional) provides a platform to directly
interface with industry leaders and develop both technical and organisational expertise. Class sizes are smaller, providing personalised support and unparalleled access to Bond
University's Macquarie Trading Room and Bloomberg data-sourcing terminals. Focus within this program is on strategically sound recommendations and data-driven business decisions.
PROGRAM INFORMATION
SUBJECT INFORMATION*Please note that the Professional Portfolio or Professional Development subject is a 20-week, 45-credit point subject and is taken in the last semester of the program once all other
coursework subjects have been completed. The Career Development Centre will provide assistance in choosing the relevant professional subject prior to your last semester.
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Program structure and sequence plans
BN-13133 Master of Business Data Analytics (Professional)Version 1 Masters Coursework
Total Subjects 13 Total Credit Points 165 Cricos Code 098314E
Structure 8 Required Subjects 5 Directed Elective Subjects
Available Code Title Assumed Knowledge Requisite
You must complete the following required subjects:
J/S DTSC71-100
J/S DTSC71-200
M DTSC71-301DTSC71-200 & Further requisites in subject
outline
M/S DTSC71-302ECON71-200 & DTSC71-200 & Further
requisites in subject outline
J/M/S ECON71-200
J/M/S STAT71-112
J/M/S Business option 2
J/M/S ACCT71-600
J/M ECON71-600
J/M/S FINC71-600
M/S MKTG71-600
J/M/S Analytic option 3
M/S ACSC71-200
J/S ACSC71-304ACSC71-200 & Further requisites in subject
outline
S DTSC71-305DTSC71-200 & Further requisites in subject
outline
S ECON71-300 ECON71-200
M FINC71-302 FINC12-200 or FINC71-600
J/M/S Alt. DTSCP
S DTSC71-303 DTSC71-301 & DTSC71-302
S DTSC71-304 DTSC71-301 & DTSC71-302
J/M/S Alt. PROF
J/M/S BUSN71-701
J/M/S BUSN71-705
Assumed knowledge is the minimum level of knowledge of a subject area that students are assumed to have acquired through previous study. It is the
responsibility of students to ensure they meet the assumed knowledge expectations of a specified subject. Students who do not possess this prior knowledge are
strongly recommended against enrolling and do so at their own risk. No concessions will be made for students’ lack of prior knowledge.
Business Analytics Coding
Data Science
Machine Learning in Business
Statistical Learning and Regression Models
Econometrics
Quantitative Methods
Choose 2 subjects from the Business option
Accounting Principles
Economics for Business
Managerial Finance
Marketing Fundamentals
Choose 3 subjects from the Analytic option
Mathematical Statistics
Stochastic Modelling
Financial Trading Systems
Advanced Econometrics
Finance Applications and Analysis
Choose either DTSC71-303 or DTSC71-304
Big Data Analytics Case Studies
Advanced Big Data Projects
Choose either BUSN71-701 OR BUSN71-705
Professional Portfolio
Professional Development
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