Joint lead time and price quotation : dynamic or static?

Intuitively, quoting dynamic lead time and price to customers based on real-time system state provides more efficient capacity utilization and increases revenue compared with quoting static lead time and price. However, dynamic quotation may require higher operational costs for the firm and it is often inconvenient to customers. This study aims to compare dynamic and static lead time and price quotations under fixed capacity and different potential demand rates. We hypothesize that there exists a potential demand rate under which the additional costs of dynamic quotation and the additional profit from dynamic quotation are equal. Thus static quotation may yield better performance under certain potential demand rates. We use an M/M/1 queuing model to model the supply system of a firm and formulate profit maximization models in an average reward criterion under both static and dynamic lead time and price quotations. Numerical analyses are presented to illustrate performances of both static and dynamic lead time and price quotation and thus find the threshold potential demand rate. Besides, we study performance of two different kinds of dynamic lead time quotation and find that when firm can decide their price, performance of dynamic lead time quotation is good enough and when firm cannot decide their price, the dynamic lead time quotation is good only when lead time sensitive factor is small and potential demand rate is big

Order Acceptance and Scheduling: A Taxonomy and Review

Over the past 20 years, the topic of order acceptance has attracted considerable attention from those who study scheduling and those who practice it. In a firm that strives to align its functions so that profit is maximized, the coordination of capacity with demand may require that business sometimes be turned away. In particular, there is a trade-off between the revenue brought in by a particular order, and all of its associated costs of processing. The present study focuses on the body of research that approaches this trade-off by considering two decisions: which orders to accept for processing, and how to schedule them. This paper presents a taxonomy and a review of this literature, catalogs its contributions and suggests opportunities for future research in this area

A Digital Twin Framework for Production Planning Optimization: Applications for Make-To-Order Manufacturers

In this dissertation, we develop a Digital Twin framework for manufacturing systems and apply it to various production planning and scheduling problems faced by Make-To-Order (MTO) firms. While this framework can be used to digitally represent a particular manufacturing environment with high fidelity, our focus is in using it to generate realistic settings to test production planning and scheduling algorithms in practice. These algorithms have traditionally been tested by either translating a practical situation into the necessary modeling constructs, without discussion of the assumptions and inaccuracies underlying this translation, or by generating random instances of the modeling constructs, without assessing the limitations in accurately representing production environments. The consequence has been a serious gap between theory advancement and industry practice. The major goal of this dissertation is to develop a framework that allows for practical testing, evaluation, and implementation of new approaches for seamless industry adoption. We develop this framework as a modular software package and emphasize the practicality and configurability of the framework, such that minimal modelling effort is required to apply the framework to a multitude of optimization problems and manufacturing systems. Throughout this dissertation, we emphasize the importance of the underlying scheduling problems which provide the basis for additional operational decision making. We focus on the computational evaluation and comparisons of various modeling choices within the developed frameworks, with the objective of identifying models which are both effective and computationally efficient. In Part 1 of this dissertation, we consider a class of Production Planning and Execution problems faced by job shop manufacturing systems. In Part 2 of this dissertation, we consider a class of scheduling problems faced by manufacturers whose production system is dominated by a single operation

Design requirements for SRB production control system. Volume 5: Appendices

A questionnaire to be used to screen potential candidate production control software packages is presented

Supply chain design: a conceptual model and tactical simulations

In current research literature, supply chain management (SCM) is a hot topic breaching the boundaries of many academic disciplines. SCM-related work can be found in the relevant literature for many disciplines. Supply chain management can be defined as effectively and efficiently managing the flows (information, financial and physical) in all stages of the supply chain to add value to end customers and gain profit for all firms in the chain. Supply chains involve multiple partners with the common goal to satisfy customer demand at a profit. While supply chains are not new, the way academics and practitioners view the need for and the means to manage these chains is relatively new. Very little literature can be found on designing supply chains from the ground up or what dimensions of supply chain management should be considered when designing a supply chain. Additionally, we have found that very few tools exist to help during the design phase of a supply chain. Moreover, very few tools exist that allow for comparing supply chain designs. We contribute to the current literature by determining which supply chain management dimensions should be considered during the design process. We employ text mining to create a supply chain design conceptual model and compare this model to existing supply chain models and reference frameworks. We continue to contribute to the current SCM literature by applying a creative application of concepts and results in the field of Stochastic Processes to build a custom simulator capable of comparing different supply chain designs and providing insights into how the different designs affect the supply chain’s total inventory cost. The simulator provides a mechanism for testing when real-time demand information is more beneficial than using first-come, first-serve (FCFS) order processing when the distributional form of lead-time demand is derived from the supply chain operating characteristics instead of using the assumption that lead-time demand distributions are known. We find that in many instances FCFS out-performs the use of real-time information in providing the lowest total inventory cost

Manufacturing strategy, product customisation and the marketing/manufacturing interface

The manufacturing strategy literature is reviewed and it is found to centre on content and process models. However, a number of other issues are present in the literature whose relationship to the central process and content models is less clear. These include the trade-off, focus, flexibility, and generic manufacturing strategies. It is noted that the manufacturing strategy literature does not fully address product customisation. The literature relating to the interface between marketing and manufacturing is found to concentrate either on the identification of conflict areas, or on strategic reconciliation between the functions. Writers in this field do give greater emphasis to product customisation. A case-study method is adopted for the research and the design involves four firms in varying industries. The firms manufacture fork-lift trucks, microswitches, telephone switching systems and diaries, respectively. The case-studies comprise quantitative and qualitative data, and each case chapter includes case-specific analysis. The analysis of all the cases finds that customisation has a very important effect on manufacturing performance. The firms have inconsistencies within their manufacturing strategies, but these are found to rest not only on the firms' manufacturing products with different volume requirements in the same plant, but also on the fact of some of the products being custom-designed. The interface between marketing and manufacturing is found to be more complex and variable than the literature would suggest. The role that customised products play in relationships with customers also varies, although this is inconsistently recognised by the firms.Based on the case-data, a model of product customisation is proposed. This incorporates customisation, flexibility, product architecture, the manufacturing strategy trade-off and the competitive criteria

Maintenance Centered Service Parts Inventory Control

High-tech capital goods enable the production of many services and articles that have become a part of our daily lives. Examples include the refineries that produce the gasoline we put in our cars, the photolithography systems that enable the production of the chips in our cell phones and laptops, the trains and railway infrastructure that facilitate public transport and the aircraft that permit us to travel long distances. To prevent costly production disruptions of such systems when failures occur, it is crucial that service parts are readily available to replace any failed parts. However, service parts represent significant investments and failures are unpredictable, so it is unclear which parts should be stocked and in what quantity. In this thesis, analytical models and solution methods are developed to aid companies in making this decision. Amongst other things, we analyze systems in which multiple parts need replacement after a failure, a situation that is frequently encountered in practice. This affects the ability to complete repairs in a timely fashion. We develop new modeling techniques in order to successfully apply scalable deterministic approaches, such as column generation techniques and sample average approximation methods, to this stochastic problem. This leads to solution techniques that, unlike traditional methods, can ensure that all parts needed to complete maintenance are readily available. The approach is capable of meeting the challenging requirements of a real-life repair shop

Manufacturing planning and operations optimisation for mass customisation manufacturing using computational intelligence.

Doctorate of Philosophy in Engineering (Mechanical). University of KwaZulu-Natal, Durban 2015.This study determined whether an Advanced Manufacturing System could be optimised, more effectively than by traditional methods, using new and novel computational intelligence techniques. An Advanced Manufacturing System can be described as highly automated and highly complex systems that strive for global competitiveness. In the context of this study, these systems aim to compete in a Mass Customisation Manufacturing market. Traditional optimisation methods refer to methods based on mathematical models, experience, or industry best practice. Computational Intelligence refers to computational methods inspired by natural systems and processes. This includes, but is not limited to, evolutionary intelligence, Artificial Neural Networks, swarm intelligence, and fuzzy systems. This study investigated the optimisation of the manufacturing system from both a planning and an operations perspective. Research was carried out to identify Computational Intelligence paradigms and algorithms for Advanced Manufacturing System planning and operations optimisation. Static and dynamic simulation models of an Advanced Manufacturing System, for the respective perspectives, have been developed in order to simulate a manufacturing system designed to produce a hypothetical range of customisable men’s wristwatches on a mass scale at a competitive cost. A new Biogeography-Based Optimisation algorithm was developed to optimise an aggregate production plan using static simulation models. This algorithm was implemented to find the lowest production cost for the wristwatch production system case study. This algorithm produced a lower cost plan than a Simulated Annealing algorithm with a lower impact on workforce. A new Distributed Dynamic Selection Rule Strategy was developed for optimising production scheduling using dynamic simulation models. This new strategy was inspired by the Harmony Search principle and was based on traditional selection rules for scheduling. This strategy was able to produce statistically significantly lower average order lead times than three out of four traditional selection rules tested

Supply chain design in the volatile semiconductor capital equipment industry

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2002.Includes bibliographical references (leaf 69).As companies outsource more manufacturing and design responsibilities to external vendors and therefore become less vertically integrated, the role of supply chain management becomes increasingly complex. Its role is particularly difficult when product generation follows a serial process flow, with the supply chain function residing at the end and where it inherits poorly defined supplier relationships. A more integrated approach that seeks to proactively design the supply chain during product generation is required. Central to this integrated approach is the timely exchange of information both within the company, between R&D and procurement, and external to the company, between procurement and its suppliers. The timing of the information flow is crucial. It needs to occur before the company is locked into a single supplier and when its bargaining power is the highest. It also needs to occur in a manner that does not slow down the product development process. In practice, that means that specific information needs to be exchanged and committed to prior to supplier selection. Ultimately, the information exchange described in this thesis leads to improved supplier relations that enable the company to shift its procurement practices from the tactical approach of buying materials to the strategic approach of buying supply services. The research for this thesis was conducted at a partner company of the Leaders for Manufacturing (LFM) program. The company manufactures test equipment used in the semiconductor industry. Due to the highly cyclical and unpredictable nature of this industry, supply chains that can guarantee responsiveness and availability are desirable. The supply chain design recommendations proposed in this thesis are based on an analysis of a recent product generation program at the company. By continuing to implement these recommendations, the company should benefit from shorter product development cycle times, smoother production ramps, improved customer service levels and lower sourcing costs.by Jens P. Voges.S.M.M.B.A