Alfred L. Guiffrida

Learning curves for imperfect production processes with reworks and process restoration interruptions

Many production processes are not defect free, and reworks are unavoidable. This makes the assumption of the Wrights learning curve [Wright, T., 1936. Factors affecting the cost of airplanes. Journal of Aeronautical Science 3 (2), 122-128] that all units produced are of acceptable quality impractical, suggesting a linkage between quality and learning to be inevitable. The quality learning curve (QLC) developed by Jaber and Guiffrida [Jaber, M.Y., Guiffrida, A.L., 2004. Learning curves for processes generating defects requiring reworks. European Journal of Operational Research 159 (3), 663-672] is a modification of the Wrights learning curve for processes that generate defects that can be reworked. This paper investigates the QLC for the assumption that the production process is interrupted for quality maintenance to bring the process in control again. New learning curves are developed with numerical examples provided and results discussed.

A review of inventory lot sizing review papers

Purpose - – This paper aims to give a comprehensive review, summary, and discussion on inventory models that have appeared in the literature. During these past ten decades, no seminal paper reviewing the field of inventory lot sizing has even been published. This limitation has been identified in the literature by several researchers over the years, with the sheer volume of the number of published inventory lot sizing models acting as a factor which has limited a research endeavor to review the literature on inventory lot sizing models. Design/methodology/approach - – This article reviews research on inventory lot size models and provides a review of previously published literature review papers on inventory models. Based on this initial review, the literature extending current research practices on inventory modeling in supply chains and in sustainable practices is presented. Directions for expanding research in these two areas are examined in light of concerns expressed in the historical use of inventory models and in light of a new inventory research paradigm. Findings - – In our paper, we have adopted a novel strategy to overcome this limitation by focusing our review on a review of inventory lot sizing review papers. Originality/value - – By adopting the methodology of reviewing published inventory review papers, we can contribute a comprehensive review of the inventory lot sizing literature that serves to provide in one paper a consolidation of inventory research that can serve as a single source to keep researchers up to date with the research developments in inventory lot sizing models. We also identify gaps in the field which could stimulate new research agendas in the areas of supply chain management and sustainable inventory practices.

The Effect of RFID On Inventory Management and Control

Our thesis is that the evolution of information technology (IT) facilitates the flow of information, which in turn may reduce the variance of an inventory system, and hence its cost. We use radio-frequency identification (RFID) as a paradigm. RFID is the latest application of IT to tracking goods and services or anything for that matter, including human beings. It is an evolution from bar code and palette technology, and, in this chapter, we present the argument that RFID is superior in reducing the mean and variance of inventory cycle times. As inventory cost is a function of these (among other variables, such as unit holding and shortage costs), we show that RFID reduces this cost. Also, because RFID leads to rapid transmission of data, it would help avoid excessive inventories and shortages, further reducing total inventory cost. We argue that RFID is superior to existing identification technologies according to mean-variance stochastic dominance. We discuss the ethical implications and the societal trade-offs inherent in RFID, as society must decide how much of its privacy it is willing to curtail in the pursuit of lower prices versus physical security.

Carbon emissions comparison of last mile delivery versus customer pickup

The last mile problem comprises one of the most costly and highest polluting segments of the supply chain in which companies deliver goods to end customers. The recent trend towards green supply chains and social and environmental responsibility has led to many new green initiatives. One business strategy gaining popularity involves retailers offering home delivery. This paper performs a comprehensive comparison of carbon emissions resulting from conventional shopping involving customer pickup with trip chaining versus e-commerce-based online retailing involving last mile delivery to customers’ homes. The break-even number of customers for carbon emissions equivalence is determined and analysed for the feasibility of last mile delivery at a desired service level based on the radius of the demand region and the delivery time available. A methodology for calculating the difference in expected carbon emissions is formulated and demonstrated to quantify which method has the least harmful impact on the environment.

Observations on the economic manufacture quantity model with learning and forgetting

The economic order (manufacture) quantity model with learning and forgetting has attracted the attention of researchers since the 1960s. All the models developed have limitations, of which two will be addressed in this article. First, the models found in the literature do not address the problem of when the learning exponent b approaches or exceeds the value 1, where these models are mathematically invalid for the special cases of b=1 and 2, and not investigated for the cases 1 2. Second, the models found in the literature assume that the holding cost per unit is fixed even though the unit production cost is decreasing because of learning. This limitation would suggest producing in smaller lot-sizes than their optimal values. Mathematical models are developed, and existing learning models are revised to overcome these limitations. Numerical examples are presented with results discussed.

The effect of human factors on the performance of a two level supply chain

Many studies have addressed the issue of coordination in a supply chain. Coordinating mechanisms such as joint lot sizing models, quantity discounts and delay in payments have been used to achieve coordination in a supply chain. An important omission in this literature is the role of human factors, in particular inspection errors and learning, as a tool to improve coordination in a supply chain. In this paper, two coordination mechanisms found in the literature are integrated into a model for a two-level supply chain in which the incoming quality level of raw materials provided to a vendor by a set of suppliers is not perfect. The model addresses supply chain coordination by specifically investigating the role of different human factors on the total cost of the supply chain. These factors are: (a) type I and type II inspection errors; (b) learning in the production process; and (c) learning in quality at the suppliers’ end. Numerical examples are used to compare the costs of the three extensions with the base model (with no defectives).

An Economic Model for Justifying the Reduction of Delivery Variance in an Integrated Supply Chain

Abstract This paper addresses the economic impact of improving delivery performance in a serial make-to-order supply chain when delivery performance is evaluated with respect to a delivery window. Building on contemporary management theories that advocate variance reduction as the critical step in improving the overall performance of a system, an expected cost model is developed that financially quantifies the benefit of reducing delivery variance to the final customer in a serial supply chain. The objective of the model is to determine the variance level that minimizes the costs associated with untimely delivery (expected earliness and lateness) and the investment cost required for reducing the delivery variance. A logarithmic investment function is used and the model solution involves the minimization of a convex-concave total cost function. Numerical examples are provided to illustrate the model and the solution procedure.

A modelling framework for improving supply chain delivery performance

The evaluation of delivery performance is a crucial component in the overall management and control of a supply chain. The main objective of this research is to develop a framework that can be used to improve the delivery performance of a supplier to the end customer in a supply chain. The framework provides a bound on the financial investment required to make improvement to the delivery process. A variance reduction modelling approach is used that directly incorporates the uncertainty in the delivery time distribution into a financial delivery performance metric. The framework is demonstrated using numerical illustrations.

A Cost-Based Model for Improving Customer Waiting Times

The effective management of a service organization requires measuring system performance on many attributes. Customer waiting time is inherent to nearly all service operations and represents a system attribute that is of high concern to both the customers who engage service and the managers of the service operation who are responsible for providing services. Effective performance measures of all system attributes are required to improve service quality. In this paper we present a cost-based, performance model for evaluating the expected cost of untimely customer waiting times for services within a service organization. The present worth of the expected costs due to untimely waiting that accrue over a finite time horizon provide management with input for justifying financial investment to support a continuous improvement program to improve service quality through the reduction of the variability in customer waiting time.

The efficacy of routing and flexibility on financial performance within an international manufacturing setting

Purpose The purpose of this paper is to extend the developing body of knowledge on supply chain performance by addressing the impact of resource commitment (RC), product route efficiency (PRE), and manufacturing flexibility (MF) on a firm’s financial performance (FP) has a direct impact on supply chain operations. Design/methodology/approach Survey questionnaires were developed in conjunction with literature guidance. Exploratory and confirmatory factor analysis was used in conjunction with structural equation modeling to give a robust analysis of the problem setting. Findings Discoveries herein indicate that committing resources in itself is insufficient to adequately increase FP over the long term. However, the mediating variables of MF and PRE were found to significantly improve a firm’s bottom line. Originality/value Prior research has been somewhat lacking and inconsistent with regards to the nature of causal and mediating relationships found between RC, PRE, MF, and a firm’s financial performance. Given the increasing global nature of competition, understanding the relationships between potential factors that could positively impact a firm’s FP has a large potential direct impact and benefit on supply chain operations.