Risk analysis and assessment for make-to-order manufacturing

Based on the characteristics of make-to-order manufacturing, risks in enterprises are analyzed, which are encountered when receiving orders. Dividing the whole process into three stages, this paper provides a qualitative explanation of the risky factors, failure rate, risk level and changes of each stage, and then provides a mathematic model of quantitative analysis by using fuzzy sets and an analytical hierarchy process. In the light of the relationship among the three stages, a formula for calculating risk levels of orders is worked out. Meanwhile, both economic and non-economic losses due to an order failure are considered in the assessment system. An actual case is analyzed using the described method. Suggestions for risk prevention or loss reduction are given.

A bi-level optimization for a make-to-order manufacturing supply chain planning:a case in the steel industry Lanndon

This paper presents an actual case application of a newly developed gametheoretic model in analyzing a single manufacturer-many supplier,multi-period,make-to-order supply chain with fuzzy parameters.The supply chain under consideration comprises an exclusive supplier for every component required by the manufacturer in producing its product.In certain instances,some supply chains enable the manufacturer to opt for a third-party subcontractor to produce a portion of its demand.We assume that the supply chain faces a price and lead-time-sensitive demand,which is relevant in a make-to-order environment.The vertical interaction within the supply chain is played as a Stackelberg game,where the manufacturer is considered the leader and the suppliers as the followers.Results show some important managerial insights in supply chain planning under a make-to-order condition.

Optimization Model in Manufacturing Scheduling for the Garment Industry

The garment industry in Vietnam is one of the country’s strongest industries in the world.However,the production process still encounters problems regarding scheduling that does not equate to an optimal process.The paper introduces a production scheduling solution that resolves the potential delays and lateness that hinders the production process using integer programming and order allocation with a make-to-order manufacturing viewpoint.A number of constraints were considered in the model and is applied to a real case study of a factory in order to viewhowthe tardiness and latenesswould be affected which resulted in optimizing the scheduling time better.Specifically,the constraints considered were order assignments,production time,and tardiness with an objective function which is to minimize the total cost of delay.The results of the study precisely the overall cost of delay of the orders given to the plant and successfully propose a suitable production schedule that utilizes the most of the plant given.The study has shown promising results that would assist plant and production managers in determining an algorithm that they can apply for their production process.

Rule based vs Optimization based Workload Control with and without Exogenous Lead Times:An Assessment by Simulation

Order release is a key production planning and control function,specifically in high variety contexts.A large literature on release methods that balance the workload consequently emerged.These Workload Control methods can be rule based,using a simple greedy heuristic,optimization based or optimization based with lead times that are exogenous.Although all three types of methods have the same objective,their performance has never been compared.Using simulation,this study shows that a better on time delivery performance of jobs can be achieved by the two optimization based release methods.Most importantly,optimization based methods that assume lead times to be exogenous significantly outperform alternative methods in terms of tardiness performance.Rule based and optimization based Workload Control without exogenous lead times overemphasize average lateness reduction,which leads to sequence deviations that offset performance improvements through balancing.In contrast,Workload Control methods that assume lead times to be exogenous limit sequence deviations,which leads to a significant reduction in dispersion of lateness.This has important implication for the future design of order release methods,and managerial practice.