This chapter highlights the contributions of this research and explains the limitations of this study. It also provides some ideas for future research opportunities.
In this study, a three-dimensional flexibility framework was first developed for tactical SC planning. This includes supply flexibility, manufacturing flexibility and distribution/logistics flexibility dimensions. A number of flexibility options were identified in relations to the flexibility dimensions.
Flexibility options associated with supply flexibility are make-and/or-buy decisions and sourcing decisions where the former option refers to the use of outsourcing strategy along with in-house production of finished products, while the latter refers to the use of multiple suppliers for raw material and/or components. The manufacturing flexibility dimension contains: process flexibility option or the ability of the firm to manufacture multiple product types, production capacity expansion option using overtime or additional shifts as well as backlogging option allowing the firm to deliver the finished product at a later period. The distribution/logistics dimension addresses flexibility options related to the transportation of finished products to customers using multiple modes and routes for transportation as well as the use of multiple transport carriers. This dimension also includes the storage capacity expansion flexibility option which refers to the use of rental warehouses for storing finished products.
The review of past studies in Chapter 2 indicated that the identified flexibility options have been incorporated in the past modelling efforts mostly in a sole dimension or two of the dimensions. It was observed that less attention has been paid to incorporate flexibility in the three flexibility dimensions in SC planning, especially in a relative comparison with various levels of flexibility. However, a flexible SC needs to incorporate multiple flexibility options in key SC processes including procurement/sourcing, manufacturing and distribution/logistics (Merschmann and Thonemann 2011; Vickery et al. 1999). Although few studies incorporate flexibility options in the three dimensions, no SC planning model was found that has
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incorporated all the important flexibility options identified in the three-dimensional framework.
A planning model was therefore developed to investigate this complex decision as an MINLP for tactical SC planning in a three-echelon network by incorporating the identified flexibility options in the three-dimensional flexibility framework. Thus, the study contributes to the literature by filling this gap by developing an optimisation model for SC planning which has incorporated the identified flexibility options outlined in the three-dimensional framework. The objective function of this model minimises the total cost of the SC. This study also provided insight on how to incorporate these important flexibility options to SC planning models.
Another contribution of this study is design of a new unique solution approach based on the CE method to solve the developed SC planning model. A modified CE method was designed and used to determine the value of binary variables in set Type ।. By determining the value of binary variables Type ।, the original MINLP model was converted to a MILP model. The MILP model was then solved using CPLEX solver and an optimal solution was found.
The proposed model was used to investigate the impacts of adjusting flexibility options by obtaining various levels of flexibility on the overall performance of the model using two important performance measures that included the total cost of SC and the service level. Four scenarios were investigated against these performance measures and it provided insight for decision-makers on how adjusting flexibility options can influence the overall performance of the SC.
Data from a real-world industrial company which manufactures a range of flange products were applied to the model and the impacts of SC planning under the four considered flexibility scenarios were investigated. The model was solved under each scenario and an optimal solution was obtained using the proposed solution approach.
It was found that Scenario 2 which uses a single supplier and multiple transport carriers resulted in the highest increase in the total cost compared to Scenario 1 which uses a single supplier and single transport carrier. But, this scenario provided an improved service level. Scenario 3 which uses a single supplier and multiple transport carriers resulted into an increase in the total cost of the SC; that is slightly lower than that observed in Scenario 2. The service level was enhanced in this scenario as well. However, the lowest increase in the total
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cost was observed in Scenario 4 where the highest improvement in the service level was observed.
The results revealed that (1) adjusting flexibility to a higher level comes with cost or in other words flexibility does not come free, and (2) flexibility-related decisions in one SC process must be made with respect to the achievable/available flexibility options in other SC processes. Although a slight increase in the overall cost of the SC was observed by introducing more flexibility options to Scenario 1, the service level can be significantly augmented. In addition, it was observed that a part of increase in the overall SC cost was compensated through a reduction in the sum of other costs in the SC. From this observation, an important insight for decision-makers is that the use of multiple flexibility options can provide a broader degree of freedom as more alternatives become available when seeking the SC cost trade-off.
In this research, therefore, the objectives listed in Chapter 1 have been achieved. This includes developing a mathematical model for SC planning with multiple flexibility options listed in the developed three-dimensional framework, optimising the model using a new unique solution approach and evaluating the impacts of adjusting two important flexibility options on the overall performance of the total cost of the system.