Cross Training Policies in Field Services

Abstract

As the trend towards more after sales services progresses through the industrial equipment industry, OEMs are now offering comprehensive service contracts in which they take full responsibility for the functioning of their customers' machines. The growing responsibilities allow for more leeway in determining how to maintain the machinery. At the same time the OEM is directly effected by the success of its maintenance operations. This is certainly the case for capacity decisions in its field operations, which is the focus of this paper. One of the most important capacity decisions in field service operations is determining the training level of technicians. A field service organization can employ fully cross trained technicians which are trained to execute any service job. However, training and retaining these employees can be very expensive. Therefore, it can be cost effective to use dedicated technicians who received a focused training enabling them to perform a limited range of service jobs. We conducted a simulation study of the field service operations of an OEM in the compressed air industry to be able to evaluate the possibility to deploy technicians dedicated to preventive maintenance instead of fully cross trained technicians. We analyze the cross training decision for different scenarios in which a considerable part of the installed based is covered by service contracts. Due to these service contracts, maintenance demand as experienced by the field service organization is influenced by the cross training decisions. Our contribution consists of identifying the optimal cross training policy and the factors that influence the benefits of the different workforce configurations while taking into account the effect of the capacity decisions on the maintenance demand. We succeed to do this by characterizing the failure behavior of the individual machines. We find evidence that full cross training might be especially beneficial in a field service setting even when the effect on demand is taking into account.

Workforce flexibility in operations management

“…Aksin et al [57] reviewed the literature of cross-training for call center applications. Different from × × [58,59] × × × [60][61][62][63][64] × × [65][66][67][68][69][70][71][72][73][74][75][76][77][78] × × × [79][80][81] × × × × [82] × × × [83][84][85][86][87][88] × × [89][90][91][92][93][94][95][96][97][98][99][100][101][102][103][104][105][106][107] other review papers dedicated to cross-train...…”

“…Generally, these studies simulate the system where cross-training is implemented. Also, numerical experiments are designed to compare the performance of candidate configurations in order to examine the manner in which performance is influenced by other factors such as environment, system settings, and workforce assignment policies (see [64,65,81,82,84,[94][95][96][97]100,107]). A related stream of research uses constrained optimization models to identify an optimal crosstraining configuration.…”

A simulation-based decision support system for industrial field service network planning

“…Colen and Lambrecht and Agnihothri and Mishra focus on the same decision problem and use DES to evaluate the outcomes of different qualification strategies in manpower planning. 7,33 They benchmark the strategy of deploying FTs dedicated to preventive maintenance instead of fully cross-trained FTs in different scenarios.…”

“…Daily call pattern, service types, product types, regional travel speeds, breaks, regions, round and sequential trip, dispatching alternatives Visser 29 Staffing and contracting Weekly call patterns, service contract, location-based travel times, product types, single service, spare parts delivery Rapaccini et al 15 Districting, dispatching, cross-training Daily call patterns, contracts, service types, product types, travel and work time distribution, geographic locations, spare parts demand, spare parts quantities Control variables: capacity, dispatching policy, scheduling policy, districting policy, cross-training policy, spare parts management policy Colen and Lambrecht 7 Cross-training Service types, contract, skills (product), call priorities, interdependency maintenance/breakdown, travel time approximation, round trip rules are changed, this might change the distribution of travel times significantly. In addition, state-of-the-art commercial simulation packages do not offer special functionality for modeling field services and require a high degree of customization to adequately model FSNs.…”

“…6 Because customers might be scattered all over the world, even for small companies with less than 200 customers, a highly skilled, diverse, and flexible workforce that can deliver service timely all over the world is required. 7 In addition, companies face problems when they comply with varying performance targets for different customers, e.g., response times that have to be met on a case-by-case basis. 2,8 Today, most methods used in field service network (FSN) planning in practice are 'outdated and overly simplistic'.…”