Moduł oferowany także w ramach programów studiów:
Informacje ogólne:
Nazwa:
Advanced Planning in Operations Management
Tok studiów:
2016/2017
Kod:
ZZP-2-405-ZF-s
Wydział:
Zarządzania
Poziom studiów:
Studia II stopnia
Specjalność:
Zarządzanie finansami
Kierunek:
Zarządzanie
Semestr:
4
Profil kształcenia:
Ogólnoakademicki (A)
Język wykładowy:
Angielski
Forma i tryb studiów:
Stacjonarne
Osoba odpowiedzialna:
dr hab. inż. Kaczmarczyk Waldemar (wkaczmar@zarz.agh.edu.pl)
Osoby prowadzące:
dr hab. inż. Kaczmarczyk Waldemar (wkaczmar@zarz.agh.edu.pl)
Krótka charakterystyka modułu

This course provides an accessible introduction to standard quantitative methods for planning and scheduling of production and logistic operations.

Opis efektów kształcenia dla modułu zajęć
Kod EKM Student, który zaliczył moduł zajęć wie/umie/potrafi Powiązania z EKK Sposób weryfikacji efektów kształcenia (forma zaliczeń)
Wiedza
M_W001 Students know standard quantitative methods, optimisation models and information systems applied to enterprise wide operational planning and supply chain coordination. ZP2A_W13 Kolokwium,
Wykonanie projektu
M_W002 Students know basic modelling techniques of management science applied in planning and scheduling of production and logistic operations. ZP2A_W12 Kolokwium,
Wykonanie projektu
Umiejętności
M_U001 Students are able to determine basic plans and schedules for typical production and logistic operations. ZP2A_U08, ZP2A_U12 Kolokwium,
Wykonanie ćwiczeń,
Wykonanie projektu
M_U002 Students are able to identify the type of a production or logistic process, to choose and implement appropriate optimisation model for arising planning or scheduling problem. ZP2A_U04 Kolokwium,
Wykonanie ćwiczeń,
Wykonanie projektu
Kompetencje społeczne
M_K001 Students are able to acquire knowledge by oneself. ZP2A_K07 Wykonanie projektu
M_K002 Students can be leaders of small project teams and are able to cooperate with professionals of different fields. ZP2A_K02 Wykonanie projektu
Matryca efektów kształcenia w odniesieniu do form zajęć
Kod EKM Student, który zaliczył moduł zajęć wie/umie/potrafi Forma zajęć
Wykład
Ćwicz. aud
Ćwicz. lab
Ćw. proj.
Konw.
Zaj. sem.
Zaj. prakt
Zaj. terenowe
Zaj. warsztatowe
Inne
E-learning
Wiedza
M_W001 Students know standard quantitative methods, optimisation models and information systems applied to enterprise wide operational planning and supply chain coordination. + + - + - - - - - - -
M_W002 Students know basic modelling techniques of management science applied in planning and scheduling of production and logistic operations. + + - - - - - - - - -
Umiejętności
M_U001 Students are able to determine basic plans and schedules for typical production and logistic operations. + + - - - - - - - - -
M_U002 Students are able to identify the type of a production or logistic process, to choose and implement appropriate optimisation model for arising planning or scheduling problem. + + - + - - - - - - -
Kompetencje społeczne
M_K001 Students are able to acquire knowledge by oneself. - + - - - - - - - - -
M_K002 Students can be leaders of small project teams and are able to cooperate with professionals of different fields. - + - + - - - - - - -
Treść modułu zajęć (program wykładów i pozostałych zajęć)
Wykład:

Managers and information technology professionals should understand basic methods of enterprise wide operational planning and supply chain coordination. This course provides an accessible introduction to standard quantitative methods for planning and scheduling of production and logistic operations, basic modelling techniques, optimisation models and information systems applied in operational planning. Basic outcome of this course is understanding of various planning problems and models, their objectives and constraints, chances which give us advanced planning systems and their limitations. Mathematical models are in the background. Assignments give students hands-on experience at developing models and solving problems. Course software and e-books are available to download.
.
1. Mixed integer programming (MIP): standard models and tools.
2. Sales and operations planning (SOP) .
3. Operational planning:
. 3.1master production scheduling (MPS),
. 3.2 material requirements planning (MRP I),
. 3.3 manufacturing resource planning (MRP II).
4. Optimisation models for replenishment planning:
. 4.1 economical order quantity (EOQ),
. 4.2 inventory policies for probabilistic demand,
. 4.3 dynamic lot-sizing problem.
5. Optimisation models for production planning:
. 5.1 lot-sizing and scheduling problems,
. 5.2 resource-constrained project scheduling problems (RCPSP),
. 5.3 machine scheduling problems,
. 5.4 safety stocks, lead times and due date setting.
6. Optimisation models for distribution planning:
. 6.1 inventory routing problems,
. 6.2 production and distribution coordination models.
7. Advanced planning systems (APS):
. 7.1 general characteristics and structure,
. 7.2 decomposition and aggregation,
. 7.3 integration and coordination,
. 7.4 collaboration,
. 7.5 implementation,
. 7.6 case studies.

Spreadsheet and MIP models:
1. SOP,
2. MRP II,
3. lot-sizing and scheduling problems,
4. resource-constrained project scheduling problems (RCPSP),
5. machine scheduling problems,
6. inventory routing problems,
7. production and distribution coordination models,
8. case studies.

The lecture is carried out as an e-learning course.

Ćwiczenia projektowe:

(In computer laboratory, in the first part of the semester)

1. Introduction to mixed integer programming (MIP): standard models and tools.
Determining plans “by hand” in spreadsheet and with help of solver for models described in spreadsheet (OpenSolver) or in algebraic modelling language (AMPL, GLPK):
2. SOP,
3. MRP II,
4. lot-sizing and scheduling problem,
5. resource-constrained project scheduling problem (RCPSP).

“Optimisation” of policy parameters with help of Monte Carlo and discrete simulation for:
6. inventory control,
7. lead time setting,
8. due date setting,
9. capacity planning.

Ćwiczenia audytoryjne:

Determining plans “by hand” on the whiteboard:
1. MRP II,
2. resource-constrained project scheduling problem (RCPSP),
3. (classic) scheduling problems,
4. inventory control,
Case studies.

Nakład pracy studenta (bilans punktów ECTS)
Forma aktywności studenta Obciążenie studenta
Sumaryczne obciążenie pracą studenta 125 godz
Punkty ECTS za moduł 5 ECTS
Udział w wykładach 30 godz
Udział w ćwiczeniach audytoryjnych 15 godz
Udział w ćwiczeniach projektowych 15 godz
Przygotowanie do zajęć 35 godz
Wykonanie projektu 30 godz
Pozostałe informacje
Sposób obliczania oceny końcowej:

Exercises 20%, project (case study) 30%, written tests 50%.

Wymagania wstępne i dodatkowe:

This course is addressed to postgraduate students of management, engineering and computer science. Basics of mathematics including logic and algebra are required to participate.

Zalecana literatura i pomoce naukowe:

Literature

  1. Silver E. A., Pyke D. F., Peterson R., Inventory Management and Production Planning and Scheduling, Wiley, 1998
  2. Vollmann T. E., Berry W. L., Whybark D. C., Jacobs F. R., Manufacturing Planning and Control for Supply Chain Management, McGraw-Hill/Irwin, 2004.

Literature available for download in AGH library

  1. Drexl A., Kimms A., Lot sizing and scheduling – survey and extensions, European Journal of Operational Research, 99(2), 1997, str. 221-235.
  2. Hartmann S., Project Scheduling under Limited Resources, volume 478 of Series, str. Lecture Notes in Economics and Mathematical Systems, Springer Berlin, 1999.
  3. Neumann K., Schwindt Ch., Activity-on-node networks with minimal and maximal time lags and their application to make-to-order production, OR Spektrum, 19, 1997, str. 205-217.
  4. Stadtler H., Kilger Ch., editors, Supply Chain Management and Advanced Planning, Springer, Berlin, 2008.
  5. Voß S., Woodruff D. L., Introduction to Computational Optimization Models for Production Planning in a Supply Chain, Springer, 2006.

Course software available for download:

  1. OpenSolver for Excel: http://opensolver.org/
  2. SolverStudio for Excel: http://solverstudio.org/
  3. GPLK (with Scite): http://home.agh.edu.pl/~waldek/glpk/
Publikacje naukowe osób prowadzących zajęcia związane z tematyką modułu:
  1. Kaczmarczyk, W. (2008). Partial coordination may increase overall costs in supply chains, Decision Making in Manufacturing and Services 2(1-2): 47-62.
  2. Kaczmarczyk, W. (2009b). Practical tips for modelling lot-sizing and scheduling problems, Decision Making in Manufacturing and Services 3(1-2): 37-48.
  3. Kaczmarczyk, W. (2009c). Modelling multi-period set-up times in the proportional lot-sizing problem, Decision Making in Manufacturing and Services 3(1-2): 15-35.
  4. Kaczmarczyk, W. (2009d). Inventory cost settings in small bucket lot-sizing and scheduling models, Total Logistic Management 2: 27-36.
  5. Kaczmarczyk, W. (2011). Proportional lot-sizing and scheduling problem with identical parallel machines, International Journal of Production Research 49(9): 2605-2623.
  6. Kaczmarczyk, W., Sawik, T., Schaller, A. i Tirpak, T. (2004). Optimal versus heuristic scheduling of surface mount technology lines, International Journal of Production Research 42(10): 2083-2110.
  7. Kaczmarczyk, W., Sawik, T., Schaller, A. i Tirpak, T. (2006). Production planning and coordination in customer driven supply chains, Wybrane Zagadnienia Logistyki Stosowanej, Tom 3, Komitet Transportu Polskiej Akademii Nauk, s. 81-89.
Informacje dodatkowe:

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