Study On Mixed Model Line Balancing With Human Factors Under Make-to-Order Environment

Mixed model assembly line can be found today in many industrial environments,in many cases,these lines follow a make-to-order production operational way which is expressed in a random arrival sequence of difference product/model types to the line. The key characteristics of such line are: a few workstations,manual conveyances,highly skilled workers. In this paper the factor of human scheduling is added to consider line balancing problems along with the traditional tasks allocation among different stations. Based on forecasted market demand,a mathematical model that aims at minimizing operators cost quantity and maximizing operators arrangement controllability is presented,it is solved by a heuristic algorithm to find a solution of re-balancing problems on current mixed model assembly line.At first,transferring to equivalent single model line is to simplify the complex of multi products and multi models random to line. Then tasks are differentiated by 2 types of classification: 1) Fixed and non-fixed work station task,neighborhood search of tasks allocation is limited within the range of non-fixed work stations; 2) Flexible and non-flexible task,non-flexible task duration can be adjusted by variable number of movable operators according to the market demand rhythm. Finally,the optimized solution of task allocation/headcount/shift is found by a heuristic algorithm. Based on this solution,a further operators skills scenario is submitted to support the long term corporate employee competency system.