All hands on deck: CREWED for technology-enabled learning

The University of New South Wales’ (UNSW’s) Faculty of Engineering is introducing a new process for designing and developing blended and fully online (distance) courses, as part of action research to support curriculum renewal. The process, referred to as CREWED (Curriculum Renewal and E-learning Workloads: Embedding in Disciplines), is being used to develop key courses that add flexibility to student progression pathways. By integrating the design of learning activities with the planning and organization of teaching and support work, CREWED addresses some of the known barriers to embedding innovative use of learning technologies within disciplines. CREWED incorporates key features of two course development models from the UK, one emphasising team building and the other emphasising pedagogical planning. It has been piloted in priority curriculum development projects, to ensure that the disciplinary organizational context is supportive. One pilot is a fully online distance version of a postgraduate course. The other is a blended version of an undergraduate course. Both are core (required) courses in accredited professional engineering degree programs and were previously available only in face-to-face mode. The UNSW pilots have confirmed the importance of articulating clear pedagogical models, and of planning ahead for the resources required to put these models into practice, as part of departmental capacity building, especially where teaching has primarily been treated as an individual classroom-based activity that competes with disciplinary research for academic staff time and resources

A greedy heuristic approach for the project scheduling with labour allocation problem

Responding to the growing need of generating a robust project scheduling, in this article we present a greedy algorithm to generate the project baseline schedule. The robustness achieved by integrating two dimensions of the human resources flexibilities. The first is the operators’ polyvalence, i.e. each operator has one or more secondary skill(s) beside his principal one, his mastering level being characterized by a factor we call “efficiency”. The second refers to the working time modulation, i.e. the workers have a flexible time-table that may vary on a daily or weekly basis respecting annualized working strategy. Moreover, the activity processing time is a non-increasing function of the number of workforce allocated to create it, also of their heterogynous working efficiencies. This modelling approach has led to a nonlinear optimization model with mixed variables. We present: the problem under study, the greedy algorithm used to solve it, and then results in comparison with those of the genetic algorithms

Flexible resources allocation techniques: characteristics and modelling

At the interface between engineering, economics, social sciences and humanities, industrial engineering aims to provide answers to various sectors of business problems. One of these problems is the adjustment between the workload needed by the work to be realised and the availability of the company resources. The objective of this work is to help to find a methodology for the allocation of flexible human resources in industrial activities planning and scheduling. This model takes into account two levers of flexibility, one related to the working time modulation, and the other to the varieties of tasks that can be performed by a given resource (multi–skilled actor). On the one hand, multi–skilled actors will help to guide the various choices of the allocation to appreciate the impact of these choices on the tasks durations. On the other hand, the working time modulation that allows actors to have a work planning varying according to the workload which the company has to face