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one of the indirect factors is production planning.

The highly automated production lines of modern poultry processors process 13.500 broilers per hour. Each broiler has its own quality specifications and unique weight, which determines its destination and potential value. The destination of a broiler can end up in several different articles; a modern retail plant offers a variety of more than 500 product articles. In order to make optimal use of the potential value of each individual broiler an information system is required. A lot of attention is paid to animal welfare, food safety, quality, full traceability, water and energy consumption. The aim is to add value to poultry as effectively as possible. The overall performance of a poultry processor is depending on a lot of factors, one of the indirect factors is production planning. Production planning on a daily level is a real challenge in the poultry processing industry. The uncertainty of the demand on one side and the dynamics of the raw material supply on the other side ask for planning skills of the processor. A lot of data and an information system are used to control the production. The exact impact of planning and scheduling is difficult to determine, but enhancements of the planning performance gains big advantages. Innova is the provided information system by Marel to support planners. For now we have an interesting Master Thesis assignment for an entrepreneurial student. In order to improve the planning performance on the long term, initially the performance should be measured in order to quantify possible improvements. The assignment is to set up a method to measure the production planning performance of a retail poultry processor. The business process of production planning is known and can be used as a starting point. Determining (key) performance indicators and an overview of required vs. redundant (available) data are the most obvious deliverables. Contact information: Marel, via Rik Eshuis, or Irene Vanderfeesten.

Production Planning & Control: Vol 29, No 3 - …

Challenges in apparel production planning and control Wallace et al.

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. Ph.D. Summer 2005. Thesis: “Multi-stage stochastic programming models in production planning.” Current Position: Associate Professor, School of Business, McMaster University.


Hierarchical production planning and energy modeling …

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Applying Lean Principles to Production Scheduling | …

Troy Andrew Hallisey is an urban planner, urban ecologies specialist, GIS and geo-web developer and designer. In 2014, he graduated from the groundbreaking M.S. Design and Urban Ecologies program at Parsons The New School for Design, which seeks to reframe the study of cities and urban processes through research, community-based fieldwork and an understanding of social, economic, political, and spatial forces. Troy recently completed an internship at the United Nations Office for the Coordination of Humanitarian Affairs on the Field Information Services team where he developed several geo-web applications for easily accessing humanitarian data.

Applying Lean Principles to Production Scheduling ..

Production Scheduling, extraction sequence of mining blocks in different production periods to maximize profit over the life of the mine and subjected to different constraints, is an important aspect of any mining activity. Mine production scheduling problem can be solved using various approaches, but the best approach is one which can give an optimal result. Production scheduling solely cannot result in a proper planning thus, fleet assignment problem needs to be incorporated into production scheduling problem to have a realistic mine plan. Proper fleet assignment ensures that the fleet is not under or over utilized. Fleet assignment problem is integer type programming since, size of fleet cannot be a floating number. In this thesis, production scheduling and fleet assignment problem are solved using branch and cut algorithm. Production schedule for 4736 blocks from a case study of coal mine is done with a production period of 5 years. Solution time for solving the production scheduling problem was 48.14 hours with an NPV value of Rs 4.45938x1011. Short terms production scheduling is done for one year and the NPV value obtained was Rs 7.59796x1010 with a solution time of 57.539 minutes. Fleet assignment is done for first year and is observed that the size of dumper fleet can be reduced to 30 thus saving huge amount of initial capital investment.