Improving the Order-Picking Process in the Case Company
Gao, Bin (2018)
Metropolia Ammattikorkeakoulu
2018
Creative Commons Attribution-NonCommercial-ShareAlike 1.0 Finland
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2018112317923
https://urn.fi/URN:NBN:fi:amk-2018112317923
Tiivistelmä
This paper focuses on improving the manual order-picking process in the case company warehouse. Order picking process has long been identified as the most labor-intensive and costly activity (up to 55% of the total operating expense) for most warehouses, so as in the case warehouse. In order to operate efficiently, the order picking process needs to be robustly designed and optimally controlled.
Action research is selected as a research approach for conducting this study, which involved diagnosing, planning, taking action and evaluating activities and was a cyclical process. Furthermore, three rounds of data, including qualitative and quantitative data, were collected and analyzed using various methods to provide adequate and solid foundation.
The study is designed into 4 key steps. It starts from the current state analysis to find out the weaknesses and strengths of the order-picking process in the case company, based on the first round of data collection (Data 1). Then, combining with the outcomes of the current state analysis, this study moves to establish a conceptual framework using existing knowledge and available best practice. Thereafter, on the basis of the outcomes of the conceptual framework and the current state analysis, as well as Data 2, the initial proposal is formed and tested in the real workplace. Finally, the proposal is validated and finalized on the grounds of Data 3.
The paper shows that substantial improvements in the case company warehouse can be achieved by applying a tailored solution. Comparing to the performance of 2017, the picking productivity increased from 31.33 lines/ (labor hour) to 43.12 lines/ (labor hour), improved around 37.6%, by application of visualization management. As for reduction of travel distance, approximately 10% extra improvements could be achieved by partially applying re-slot fast moving area and zone picking. According to the rough calculation, around 2-4 pickers can be saved, comparing to the performance of 2017.
Finally, the validated proposal can also have a significant effect on the whole warehouse management and supply chain management, thus going beyond the order-picking process itself. It gives more granular knowledge to the organization and managers could better forecast the amount of work and labor cost before several months. Thus, the analysis and the proposed solution give contribution to improving the overall performance of the case company.
Action research is selected as a research approach for conducting this study, which involved diagnosing, planning, taking action and evaluating activities and was a cyclical process. Furthermore, three rounds of data, including qualitative and quantitative data, were collected and analyzed using various methods to provide adequate and solid foundation.
The study is designed into 4 key steps. It starts from the current state analysis to find out the weaknesses and strengths of the order-picking process in the case company, based on the first round of data collection (Data 1). Then, combining with the outcomes of the current state analysis, this study moves to establish a conceptual framework using existing knowledge and available best practice. Thereafter, on the basis of the outcomes of the conceptual framework and the current state analysis, as well as Data 2, the initial proposal is formed and tested in the real workplace. Finally, the proposal is validated and finalized on the grounds of Data 3.
The paper shows that substantial improvements in the case company warehouse can be achieved by applying a tailored solution. Comparing to the performance of 2017, the picking productivity increased from 31.33 lines/ (labor hour) to 43.12 lines/ (labor hour), improved around 37.6%, by application of visualization management. As for reduction of travel distance, approximately 10% extra improvements could be achieved by partially applying re-slot fast moving area and zone picking. According to the rough calculation, around 2-4 pickers can be saved, comparing to the performance of 2017.
Finally, the validated proposal can also have a significant effect on the whole warehouse management and supply chain management, thus going beyond the order-picking process itself. It gives more granular knowledge to the organization and managers could better forecast the amount of work and labor cost before several months. Thus, the analysis and the proposed solution give contribution to improving the overall performance of the case company.