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Peter Nielsen, Ngoc Anh Dung Do, Thomas Eriksen and Izabela Nielsen

Abstract

This paper presents an analysis methodology for establishing the demand stability of the planning environment faced by a company and the impact on the stability from changes to sales order. The methodology focuses on three critical planning parameters derived from customer orders: product mix, volume, and order sizes. Furthermore, the methodology links the delivery performance of a company to the changes made to sales orders. Based on a test case application of the methodology, it is concluded that by accepting changes, the demand faced by the case company has become more unstable on product mix, volume, and the number of order lines per period, while some added stability has been achieved with regards to the order size distributions. Ultimately, by applying the methodology to the case company, it is found that by changing the sales orders, the company does not improve the delivery performance.

Open access

Poul Svante Eriksen and Peter Nielsen

Abstract

In this paper an investigation into the demand, faced by a company in the form of customer orders, is performed both from an explorative numerical and analytical perspective. The aim of the research is to establish the behavior of customer orders in first-come-first-serve (FCFS) systems and the impact of order quantity variation on the planning environment. A discussion of assumptions regarding demand from various planning and control perspectives underlines that most planning methods are based on the assumption that demand in the form of customer orders are independently identically distributed and stem from symmetrical distributions. To investigate and illustrate the need to aggregate demand to live up to these assumptions, a simple methodological framework to investigate the validity of the assumptions and for analyzing the behavior of orders is developed. The paper also presents an analytical approach to identify the aggregation horizon needed to achieve a stable demand. Furthermore, a case study application of the presented framework is presented and concluded on.

Open access

Peter Nielsen, Zbigniew Michna, Brian Bruhn Sørensen and Ngoc Do Anh Dung

Abstract

Lead times and their nature have received limited interest in literature despite their large impact on the performance and the management of supply chains. This paper presents a method and a case implementation of the same, to establish the behavior of real lead times in supply chains. The paper explores the behavior of lead times and illustrates how in one particular case they can and should be considered to be independent and identically distributed (i.i.d.). The conclusion is also that the stochastic nature of the lead times contributes more to lead time demand variance than demand variance.

Open access

Morteza Zangeneh, Peter Nielsen, Asadolah Akram and Alireza Keyhani

Abstract

The aim of this paper is comparing all possible scenarios to improve the performance of agricultural supply chain (ASC). For this purpose, at first all scenarios is discussed and the main constraints, i.e. available budget and time, is considered. In this study the drivers to improve the performance of ASC is select and distribute the best agricultural service packages in the target ASC. All discussed scenarios need a selection procedure. So a multilevel approach is developed to select the best service package for each scenario. All selection methods are based on performance measurement which had been selected in first level of the approach. Fuzzy decision making and Analytic Hierarchy Process have been used for the approach. A numerical example is solved at the end of the paper to show the capability of the approach and comparing the scenarios.