3 Presentations

• 
  03:40 PM - 04:05 PM

  Digital transformation in the forest industry; a road that FPInnovations is paving it!

  • Foroogh Abasian, presenter, Manager, Digitalization, FPInnovations

  Digital transformation is a path that many industries should take to make sure the continuous growth and sustainability in the business. This rule is not excluded for the forest industry. In this presentation, firstly I will talk about how FPInnovations support forest industry from forest operations to consumer and industrial products. Afterwards, I will explain how the many years of knowledge and experiences empower us to paving a new road in forest industry on digitalization. A solution that can efficiently respond the important concern of labor shortage in the industry.
• 
  04:05 PM - 04:30 PM

  Incentive Mechanisms: An Application of the Pulp and Paper Sector

  • Mona Jazinaninejad, presenter,
  • Mohammadreza Nematollahi,
  • Azam Shamsi Zamenjani,
  • Alireza Tajbakhsh,

  The study utilizes a combination of quantitative modeling and numerical analysis to identify an appropriate subsidy program for the local government to ensure the truth-telling of pulp and paper mills under the cap-and-trade mechanism using the Lagrange model. The analysis shows that the government helps low-demand and high-demand mills, but the help for the high-demand mill leads to more sustainable decisions.
• 
  04:30 PM - 04:55 PM

  Strategic planning of private woodlots in New Brunswick : issues and challenges

  • Jules Comeau, presenter, Université de Moncton

  We describe the efforts and challenges of completing a strategic planning process for private woodlots in the Madawaska region of New Brunswick (Canada) using the Woodstock Optimization Studio. We will discuss the process of validating the Woodstock models and present some preliminary results. Multiple private woodlot owner objectives and goals are a main source of uncertainty that is specific to this context and has seen very little treatment in the scientific literature. We briefly discuss the probabilistic optimization methodologies that are likely to be best adapted to this problem.