Changeable Manufacturing - Classification, Design and Operation

This research develops the notion of environmental fit and flexibility and illustrates the importance of such fit empirically using survey data from 101 manufacturing firms. Two dimensions of environmental dynamism are identified and the fit between them and different approaches to flexibility are assessed. Hierarchical regressions provide evidence that flexibility is a stronger predictor of performance in more dynamic environments. Specifically, presence of the unpredictability or the volatility aspects of environmental dynamism each warrant the use of different types of manufacturing flexibility strategies. Statistical results are interpreted with the caveat that while implemented capability must be used to study performance effects, this study uses perceived importance scales for flexibility.

Fit, Flexibility and Performance in Manufacturing: Coping with Dynamic Environments

Uncertainty and supply chain risk: The moderating role of supply chain flexibility in risk mitigation

textEver more companies are recognizing the benefits of closed-loop supply
chains that integrate product returns into business operations. IBM
has been among the pioneers seeking to unlock the value dormant in
these resources. We report on a project exploiting product returns as
a source of spare parts. Key decisions include the choice of recovery
opportunities to use, the channel design, and the coordination of
alternative supply sources. We developed an analytic inventory control
model and a simulation model to address these issues. Our results show
that procurement cost savings largely outweigh reverse logistics costs
and that information management is key to an efficient solution. Our
recommendations provide a basis for significantly expanding the usage
of the novel parts supply source, which allows for cutting procurement
costs.

Integrating Closed-loop Supply Chains and Spare Parts Management at IBM

A production–inventory model in an imperfect production process

https://isiarticles.com/bundles/Article/pre/pdf/3633.pdf

Manufacturing flexibility and real options : A review

Valuation of product-mix flexibility using real options

Product-mix flexibility is one of the major types of manufacturing flexibility, referring to the ability to produce a broad range of products or variants with presumed low changeover costs. The value of such a capability is important to establish for an industrial firm in order to ensure that the flexibility provided will be at the right level and used profitably rather than in excess of market requirements and consequently costly. We use option-pricing theory to analyse the impact of various product-mix issues on the value of flexibility. The real options model we use incorporates multiple products, capacity constraints as well as set-up costs. The issues treated here include the number of products, demand variability, correlation between products, and the relative demand distribution within the product mix. Thus, we are interested in the nature of the input data to analyse its effect on the value of flexibility. We also check the impact at different capacity levels. The results suggest that the value of flexibility (i) increases with an increasing number of products, (ii) decreases with increasing volatility of product demand, (iii) decreases the more positively correlated the demand is, and (iv) reduces for marginal capacity with increasing levels of capacity. Of these, the impact of positively correlated demand seems to be a major issue. However, the joint impact of the number of products and demand correlation showed some non-intuitive results.

The impact of the product mix on the value of flexibility

In this chapter, we give an overview of recent literature on the planning and scheduling of refinery activities. Planning of refinery activities ranges from determining which crude oil types to acquire to which products that should be produced and sold in the market. The scheduling ranges from scheduling of crude oil unloading and blending to blending of components to finished products. This overview treats three different categories of activities: planning and scheduling of crude oil unloading and blending, production planning and process scheduling, and product blending and recipe optimization. The focus will be on identifications of problems, the models outlined for the specified problems, and the computational difficulties introduced by the models. A final section discusses an agenda for future research.

Refinery Planning and Scheduling: An Overview

Refinery operation planning is a complex task since refinery processes and inventories are tightly interconnected. We study refinery planning when ships are loaded with a blend of components and where arrival times of ships are uncertain. Any delay in ship arrival may result in overfull component tanks which results in less efficient blending alternatives, reduced process operations or even shut downs. We propose a planning approach where we use robust optimization as a decision tool. By using robust optimization uncertainty in arrival times is explicitly dealt with and the resulting plan and schedule will always be feasible. The approach includes a flexible way to describe and model uncertainties. To compare the robust approach with a traditional deterministic approach, we use a simulation process. Computational results from a case study and simulations show that the proposed methodology is substantially better than a deterministic approach.

https://link.springer.com/content/pdf/10.1057%2Fjors.2012.86.pdf

Jens Bengtsson

Papers

Manufacturing flexibility and real options : A review

Valuation of product-mix flexibility using real options

The impact of the product mix on the value of flexibility

Refinery Planning and Scheduling: An Overview

Robust planning of blending activities at refineries