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Research Symposium: New Ideas in Order Fulfilment17 September, 2008. Nottingham University Business SchoolResponsiveness is a key driver for all players in today’s supply chains — manufacturers, retailers, intermediaries and logistics partners. The combined effects of time compression, customer-driven variety, retailer-driven rapid response initiatives and supply chain reengineering are affecting many sectors. Ensuring that the right mix of products is available in the marketplace when required continues to present challenges. The challenges vary across sectors, markets and product categories. The traditional ‘textbook’ models for planning and order fulfilment need to be augmented by more flexible forms of response. The symposium explored and examined emerging and new ideas in order fulfilment in different sectors, including developments in:
Speakers
Prof. Bart MacCarthy, Professor of Operations Management, Nottingham University Business School
Here we consider order fulfillment strategies available to manufacturing companies to respond to demands for increasing levels of product variety and product customization. A new classification of these approaches is presented incorporating the standard textbook models along with newer approaches emerging from practice. We discuss one of the more flexible forms of response – open pipeline planning – and its emergence in the automotive sector. Open pipeline planning seeks to use a Build-to-Forecast approach whilst striving to meet individual customer requirements for specific variants efficiently and with speed. Some of the properties of open pipeline systems are highlighted. The relevance of the approach to other manufacturing contexts is discussed, particularly those with high variety and significant upstream pipelines of planned products.
Thomas Volling, Institute of Production and Logistics Management, University of Braunschweig
Due to a significant rise in demand, many steel companies throughout the world are producing near capacity. Production in this industry is commonly order-driven as to cope with the broad variety of products offered to the market. As a result, orders are unique in terms of capacity requirements and contribution margin. A central planning task in this setting falls into the domain of revenue management, i.e. the selection of customer orders such that the overall contribution margin is maximized. Based on the analysis of the decision situation we discuss applications of revenue management to support order fulfillment in steel manufacturing.
Nagihan Comez, Assistant Professor of Operations Management, Faculty of Business Administration,
Bilkent University
A decentralized system of two competing retailers that order and sell the same product is studied. When a customer demand occurs at a stocked-out retailer, that retailer can request a unit to be transshipped from the other retailer. If this request is rejected, the unsatisfied customer can go to the other retailer with a demand overflow probability. Each retailer maximizing his/her own profit makes two types of decisions: initially the order quantity from a manufacturer and afterwards transshipment accept/reject decisions. We show that retailers' transshipment policies are characterized by chronologically non-increasing inventory hold-back levels. Order quantity decisions form a non-cooperative game, which is studied under two cases to obtain the existence of pure strategy equilibrium. We show the retailers’ and manufacturer’s benefit from the optimal transshipment policies to be implemented. We also analytically study the magnitude of hold-back levels to derive interesting insights, such as smaller retailers and geographically distant retailers benefit more from transshipments.
Hartanto Wong, RCUK Academic Fellow, Cardiff University’s Innovative Manufacturing Research Centre (CUIMRC)
Over the past few years we have witnessed a continuously growing number of industrial applications, known as Custom Manufacturing (CM), in which manufacturers offer bespoke one-off products at relatively low cost and short delivery lead times. The most lucrative field of application for CM is currently found in the medical industry such as producing personalised hearing aids and dental products. The key enabler of CM is Rapid Manufacturing (RM), a new technique of manufacturing evolved from a family of new technologies known as Rapid Prototyping. RM is based on additive layer manufacturing technique to produce end-use products directly from the 3D CAD model data without the need for tooling. The very promising development of RM seems to be an important catalyst for expanding and enhancing CM applications in the next few years. In this paper we present stylised models to examine the viability of CM. The models capture the interplay between manufacturing and marketing decisions and are used to assess the costs / benefits of CM when compared, in particular, to the more conservative mass customization concept where customers are only given a limited number of options. Numerical examples help in identifying conditions under which pursuing CM would be more (less) beneficial
Dr Philip Brabazon / Dr Andrew Woodcock, Senior Research Fellow/Research Fellow, Mass Customization Research Centre, Nottingham University Business School
Automotive producers are aiming to make their order fulfilment processes more flexible. Opening the pipeline of planned products for dynamic allocation to dealers / customers is a significant step to be more flexible but the behaviour of such Virtual-Build-To-Order systems are complex to predict and their performance varies significantly as product variety levels change. This research investigates the potential for intelligent control of the release of orders into the pipeline, taking into account the current status of inventory (volume and mix) and of the volume and mix of unsold products in the planning pipeline, as well as the demand profile. The research is extended by applying the principles and practices of revenue management.
Prof. Linda Hendry, Professor of Operations Management, Lancaster University Management School
Workload Control (WLC) is a leading production planning and control solution for make-to-order companies; however, few successful case studies have been reported. To facilitate more widespread use, Hendry et al. (2008) identified seventeen WLC implementation issues through comparative case study analysis and described how many of these issues could be overcome in practice; however, it was concluded that WLC implementation requirements should be explored in additional settings. This paper uses these implementation issues as a checklist for embedding WLC in a small engineering company. Progress has confirmed the particular significance of twelve of the issues to an additional setting and identified a further six, including uncertainty after order release. The paper expands on how implementation issues can be overcome, e.g., by applying customer-specific strike rate values, and describes the refinement of WLC theory, e.g., to cope with rush orders. Future research will explore the impact of WLC on performance.
Dr Luc Muyldermans, Operations Management Division, Nottingham University Business School
This talk reports on Collaborative Planning, Forecasting and Replenishment (CPFR) arrangements between a large soft drink manufacturer and major retailers in the UK. The manufacturer’s sales are strongly driven by the promotions executed in the retail stores. We develop a conceptual demand reference model - a model which lists the factors, signals and events that may explain demand. These factors are then used in multiple linear regression forecasting models to predict the weekly retailers’ sales.
Prof. Aydin Alptekinoglu, SMU Cox School of Business, Dallas, Texas
Inventory pooling is at the root of many celebrated ideas in operations management - postponement, component commonality, and resource flexibility are some examples. Motivated by our experience in the after-market services industry, we propose a model of pooling with an inventory minimization objective and service level constraints. The solution of the model consists in the specification of an inventory level as well as an allocation policy that satisfies a set of differentiated service levels in the most parsimonious fashion. Our central research question is the following: What are the optimal ordering and allocation policies when a pool of inventory is used to satisfy individual service levels for multiple customers with random demands? We identify optimal policies in several cases. We explicitly show that our optimal solutions scale easily from a single period to a multiple period setup with lead time. Joint work with Nikhil Jain (Servigistics, Inc.) and Anand Paul (University of Florida)
Prof. Dr Herbert Meyr, Technical University of Darmstadt, Department of Production and Supply Chain
Management
Up to now, demand fulfillment in make-to-stock (MTS) manufacturing is usually handled by Advanced Planning Systems which fulfill orders on the basis of Available-To-Promise (ATP) inventory and either simple ATP allocation / consumption rules or deterministic planning approaches not taking into account demand fluctuations. This is in particular the case if customers are heterogeneous and segmented into different customer classes. In literature, different streams of stochastic demand fulfillment models (e.g. revenue management, inventory rationing, randomized linear programming) emerged that deal with fluctuating demand of different customer classes very successfully. However, usually they do not fit all of the specific characteristics of MTS-manufacturing, as for example storage of excess capacity and future incoming supplies. In this talk, different deterministic and stochastic approaches for MTS demand fulfillment are categorized, discussed and numerically analyzed.
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Slides