Linear programming, Operations research, Technology -- Management, Assembly-line methods -- Technolgical innovations, Assembly-line balancing
Traditional production methods have been slowly replaced by assembly lines as manufacturers are facing unprecedented pressure to produce products in a shorter cycle time and remain competitive in terms of price (Mircea, 2012). Typical modern assembly line examples include an arrangement of work stations, either linear or circular, each with predetermined tasks that must be performed in sequential order. In manufacturing plants, the assembly lines usually maintain a store of components to be assembled in the finished parts. Major factors determining the success of assembly lines are evenly split workloads between all of the stations, similar and consistent cycle times of each station, and clearly defined sequences that must be followed with high quality and efficiency (Aregawi, 2018).
The methodology used in our project to collect the data for assembly line is time study methodology. The data collection began after the line was at full production to account for new employees and reduce data skewed by startup learning curves. Sequential processes were listed or each station with parallel tasks accounted for. Since line employees were cross trained at all the stations, two readings were taken at each station to identify the reasonable time range in which tasks should be able to be completed during the normal work day with workers of varying skill levels. The maximum and minimum time readings for each task were averaged and totalled indicating the actual workload demanded of each station. The workload was divided among the workers in the station resulting in a resource input referred to as man hours.
Linear programming techniques and sensitivity analysis were used for the data analysis and optimization of the resources. Using sensitivity analysis, the shadow prices of the current production plan are identified. Also known as row duals, the shadow prices tell us how much of each resource is required to meet the next quantity of output desired. The next logical step in the TP60 assembly line is to increase daily production from 3 to 4 per day. Based on the results, the study was further extended by analyzing the data to indicate if proper line balancing is achieved necessary to reach an optimized sequential line production model.
Agarwal, Shivani; Brown, Kyle; Fritz, Jesse; Gadiraju, Harshita; and Sawant, Chaitali Sunil, "Assembly Line Assessment and Optimization" (2019). Engineering and Technology Management Student Projects. 2282.