University of Twente Student Theses


Towards control of capacity at the spare parts production of Nefit

Janssen, Guus (2012) Towards control of capacity at the spare parts production of Nefit.

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Abstract:The Spares Assembly department of Nefit (SA) produces spare parts for boilers for Nefit, Buderus, and Bosch. After moving from Buinen to Deventer, SA was unable to keep up with demand during the high season (October – April). During the low season (April - September), there was overcapacity. Both phenomena where caused by lack of knowledge on the demanded spare parts. Therefore SA could not make a reliable capacity planning for deploying employees efficiently and effectively. This led to low delivery performance while employee costs were high. The aim of this research is to find a method that allows SA to plan their workforce requirements. The planning method should be able to determine the length of the shift for each week in the planning horizon as well as the assignment of employees to workstations. SA uses 12 workstations, with each workstation corresponding to one skill in which each employee can be trained. Training on a workstation is required before an employee can operate the workstation. This training takes a certain time, dependent on the workstation. The problem to be solved in this master thesis report is therefore defined as: “How can SA create insight in the required number of employees and their skills, to ensure availability of the right skills, in the right amount, at the right time?” The workforce planning proposed is according to a deterministic model. A deterministic model has been selected as it allows planning to be accurate and reliable enough for the situation of Nefit. At the same time the computational burden of a deterministic model is smaller than for a stochastic model. The workforce planning proposed is a tactical planning model that uses known spare part demand as input. This planning allows timely assignment of employees to the required workstations, while using known demand information. The goal of the model is to minimize the total costs associated with assigning employees to functions, while finishing all demanded spare parts in time. This meets both Nefit’s objectives; delivery performance is maintained at high levels, while minimizing production costs. The proposed workforce planning uses heuristic methods designed for the situation of SA to determine who is assigned to which workstation at what moment in time. The advantage of these heuristics methods is that they create good problem solutions by using simple assignment rules. This makes the planning model computationally less burdensome than exact methods or more complicated heuristic methods. The heuristic methods ensure that production of spare parts is performed before the due date, while smoothing out peaks and valleys in demand. In case in time production is not possible all backlog is finished as soon as possible. Employee assignment is done by deploying the least skilled employees first. Assigning these employees to workstations for which it is toughest to assign an employee to, increases the chance that the remaining employees can operate the remaining workstations. These steps are repeated for all possible combinations of shift lengths over the planning horizon. The solution with the lowest costs over the entire planning horizon is selected. The proposed workforce planning is compared with the workforce planning currently used by using a test run. This test run is performed over March and April 2012, a period of two months with steady, increasing and decreasing demand, to test the behaviour of both workforce planning methods. The indicators used to measure the performance of both models are: 1. Delivery performance in percentage of products being delivered in time. 2. Costs associated with hiring, firing, training and employing of employees. Conclusions and recommendations  The proposed workforce planning is preferred over the current workforce planning because of the relatively large costs reduction of 24% while the delivery performance is decreased from 99.63% to 99.54%. By using a binominal distribution of the delivery performance, no prove was found that any significant differences between to two workforce planning models exist. Also the deviation from the target of 99.7% delivery performance did not prove to be significant.  Implementing the workforce planning is only possible when assembly times are known. This allows both the available workload as the delivered capacity to be defined in the time in days. This can be done either by SA through time registration, or by the process engineering department through MTM (methods-time-measurement) analysis.  Due to an error in the output from the ERP system, the delivery dates for each production order are incorrect. This error is to be tracked down by the planning department and the IT department to enable SA to accurately plan the best moment of production. Without these two issues resolved it is impossible for Nefit to perform proper workforce planning and achieve the desired results.  A shadow run can be used to correct the current workforce planning before full implementation of the proposed workforce planning. The shadow run also allows adjustment to the input of proposed workforce planning before full implementation.  The implementation and shadow run can best be lead by the supervisor as he will be the operator of the planning. To be able to operate the planning he has received training and is thus the most knowledgeable employee on the workforce planning.
Item Type:Essay (Master)
Nefit B.V.
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:85 business administration, organizational science
Programme:Industrial Engineering and Management MSc (60029)
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