Wed 20th October, 2021 & Wed 27th October, 2021
12:00 pm – 2:00 pm AEST
Proudly supported by
Member: $350 + gst
Non-Member: $450 +gst
Registration closes 11 October 2021
● Virtual Facilitated Workshops: 4 hours
● 2 x 2 hour sessions over two week
● Online resources
This interactive program will provide a broad overview of data-driven decision making using a decision-tree or logic flow diagram approach. The program will consist of two 2-hour interactive workshop sessions. Each session will be prefaced by some preliminary learning materials, including tasks to be completed prior to participants attending. The workshops themselves will be presented live, and will deliver further context and real-world examples, including the opportunity for participants to practice as they learn. Depending on the background of the attendees, examples might be sought directly from participants. We encourage you to come prepared with a process-related problem or decision to which there may be a data-driven solution! Additional resources and guidelines on how to use the methods presented in other situations and scenarios will be provided to facilitate offline practice for those who wish to further apply their learning.
WHO SHOULD ATTEND?
This workshop is appropriate for technical and non-technical staff. Practitioners, data generators and analysts are encouraged to attend, as are managers and supervisors who rely on data analysis performed by members of their teams when making business, process or operational decisions.
Upon successful completion of this workshop, participants should be able to:
• Identify how and when to make data-driven decisions
• Understand what tools and methods are available and applicable for making data-driven decisions
• Determine what data is required to make or assist in making a decision
• Strategically plan and execute plant trials to generate any new data required
• Collect, clean, analyse and interpret data from plant trials
• Relate the outcomes of the analysis and interpretation back to the original decision
• Understand data communication formats and how to select the most appropriate format to clearly and concisely convey the link between the data and the decision
|Dr Joanne Tanner is a chemical engineer with industry experience in control systems design and configuration (Honeywell) and chemical engineering R&D at laboratory, pilot and industrial scale (HRL Technology). She has a PhD in reaction engineering, and is currently a Research Fellow at BioPRIA, where she leads the Green Chemistry and Sustainable Processing Research Platform. Dr Tanner has also taught process control and data analysis at Undergraduate and Master levels. She is the academic representative for Monash on the Joint Chemical Engineering Committee (Victoria) and an active member of the IChemE Digitalisation Technical Advisory Group (DigiTAG)|
|Matthew O’Connor is a process and technical support engineer at the Norske Skog Boyer mill. He has a wide range of experience in pulp and paper, including mechanical pulping, deinking, paper making, wet end chemistry & deposit control, dryer optimisation, and winding. Matthew has a specialty focus of providing advanced analytics to the business, from ad-hoc analysis through to integration into routine decision making. His background is chemical engineering, and he has additional experience in life cycle analysis. Matthew has a passion for turning technical principles and data into information, insights, and knowledge to support better business decision making.|