Joel K. Jolayemi

A deterministic model for planning production quantities in a multi-plant, multi-warehouse environment with extensible capacities

Abstract We have developed a deterministic model for planning production and transportation quantities in multi-plant and multi-warehouse environment with extensible capacities. The model determines a production mix that maximizes total profit over a finite planning horizon. When production cannot meet demand due to lack of adequate resources, the model allows shortfalls to be met through subcontracting or the use of inventory. However, it does not allow subcontracting when adequate resources are available. When solved, the model produces the quantity of each product to be: (1) produced at each plant, (2) transported from each plant to each warehouse, (3) subcontracted at each warehouse, and (4) kept in inventory at each warehouse. Furthermore, it identifies the warehouses that need extensions at any period and the corresponding amounts of extensions needed. We also develop a procedure for reducing the size of the zero–one MILP problem that can be obtained during any application of the model. Numerical examples given to illustrate the model and to compare the full and the reduced versions of the model show that the model works well and that both the full and the reduced versions produce exactly the same results. Finally, we discuss the assumptions underlining the model and highlight the approaches that can be taken to eliminate or, at least, prevent errors that are associated with violations of the assumptions.

Hoshin kanri and hoshin process: A review and literature survey

This research is based on a comprehensive survey and review of hoshin kanri (HK) literature. In the research, the lists of elements that characterize HK and elements that distinguish it from the conventional strategic planning are compiled and presented. The seven steps of the hoshin process developed by the GOAL/QPC Research Committee are extended to ten. Discussions of the results of the survey and review are based on these ten steps. This enables us to cover all the key elements of the Western-type or modern HK in our discussions. Many interesting findings are obtained from the research. Most of the findings relate to the shortcomings of modern HK. These shortcomings have their roots in the ways modern HK and its processes are generally presented in literature. Modern HK is greatly shortchanged in its presentations by Western scholars. Most published works on it and its processes fail to adequately cover all the key elements and characteristics that can give it superiority and advantage over the Japanese hoshin. The shortcomings are discussed alongside suggestions and recommendations for improvements.

A mathematical programming procedure for selecting crops for mixed-cropping schemes

Abstract We have developed a new solution procedure for a mathematical — linear programming (LP) — model that can be optimized to obtain an optimum crop combination for a mixed-cropping scheme. Unlike two earlier solution procedures for this model, the new procedure does not involve the enumeration of all possible crop combinations or crop-subgroups obtainable from any set of crops under consideration for mixed-cropping. This makes it far more efficient. Instead of formulating and solving all LP problems associated with all possible crop-subgroups — as in one of the existing procedures — the new procedure formulates and solves a few LP problems with respect to a few crop-subgroups selected systematically. Many hypothetical crop-selection problems are simulated and solved to demonstrate the superiority of the procedure over the existing ones.

Convolution of independent binomial variables: an approximation method and a comparative study

Abstract This paper has developed an approximation (the J approximation) to the convolution of independent binomial variables. The paper has also compared the performances of the J approximation with the only existing one — the Speevak and Yus (SY) approximation. Many numerical examples are given with various values of proportions of success, sample sizes and sums of the number of successes. The results show that when the value of the measure of deviation (m.d.) of the proportions of success p i s are not too large, the J approximation is strikingly close to actual values and much better than the SY approximation. Although their accuracy decreases with increases in the values of the sum of the proportions of success p D , the two approximations are still good when the value of p D is as large as 0.3.

A power function model for determining sample sizes for the operations of multivariate control charts

Using the hypothesis-testing approach, we develop a model for determining sample sizes for the operation of multivariate control charts. A simple solution procedure that can be processed on any personal or small computer is also developed. The effect of correlation between pairs of variables on the performance of the model is studied. The performances of multivariate and univariate control charts are compared under the model. Before the development of the model, a brief review of multivariate test of hypothesis and multivariate control charts was done. The model is recommended for any quality control engineer who may like to specify a desired level of protection against inferior quality.

An optimal design of multivariate control charts in the presence of multiple assignable causes

In quality surveillance, it is often necessary to measure the quality of a product on more than one characteristic. Also, processes subjected to only one assignable cause are rare in practice. Hence there is need for a good technique for designing a control chart that takes account of all the relevant characteristics and different assignable causes. We present an economic model for designing a matched single-cause model from the original multiple-cause model. The results of the final computations show that, under the model, the multivariate control chart is generally more efficient than the X@?-chart.

A unified approximation scheme for the convolution of independent binomial variables

In this paper, we have developed a unified approximation scheme for computing the convolution of independent binomial variables. The development of the scheme has been based on two approximation methods: Speevaks [4] and ours [3]. The two methods have been compared and their properties studied to understand their advantages and limitations. Our knowledge of these advantages and limitations has been well exploited in developing this scheme. Under the scheme, the two methods can be applied alternatively. A criterion for determining which of them is better for a problem is developed. The scheme is found to be devoid of most of the shortcomings associated with each of the two methods and is also more accurate.

A Characterization of Lower-Tier Supplier Visibility Practices in Supplier Relationship Management

This study explores industry perspectives on lower-tier supplier visibility (LTSV) with respect to various supplier stratifications. According to the analysis of our survey data collected from 74 companies and interviews with 19 industry executives from 15 companies, we found that companies with LTSV system are willing to expand their LTSV process to its suppliers that are of lesser overall importance rather than the traditional practice of restricting such requirement to suppliers with very high level of overall importance (i.e. strategic suppliers). Our findings also show that minimizing supply chain risks (MSCR) and ensuring supply performance (ESP) are primary motivations for companies to engender LTSV. Furthermore, we found that companies adopting LTSV process for strategic and collaborative suppliers focus on MSCR, but on ESP for custom suppliers. These findings contribute to the literature of supplier relationship management (SRM) on lower-tier supplier management and also provide a guideline for the industry to create appropriate LTSV strategies.

A model for the statistical design of multivariate control charts with multiple control regions

This paper develops a statistical model for the design of multivariate control charts with multiple control regions (MCCMCR). The model produces the sample size and values of the control limits needed for the operations of MCCMCR. It allows the consumers and the producers to specify desired values for the risks and power functions that have the greatest effects on the efficiency of the chart. Numerical examples are given to illustrate the model and to study the properties of MCCMCR.

AN INTEGRATED MODEL FOR PLANNING AND MANAGING MULTI-REGIONAL MIXED-CROP FARMING SCHEMES

Abstract An integrated model has been developed for planning and managing multi-regional mixed-crop farming schemes across ecological zones. A net-present-value formula is also developed for calculating the inflation-adjusted net present value of profit per acre of each crop before using it (the adjusted net-present value of profit) as one of the inputs into the model. The model provides the required technical tool for selecting the best sets of crop-combinations and for determining the optimum number of acres of each selected crop to be cultivated in different ecological zones under a multi-regional mixed-crop farming scheme. It also determines the quantity of each harvested crop to be shipped from each of the ecological regions or zones to each of the warehouses covered by the scheme. Furthermore, it determines the amount of expansion/extension needed by each warehouse. The model centralizes all available resources for optimum uses in all the regions. A very simple procedure for optimizing the model is presented. Numerical examples are given to illustrate the model and to investigate the quality of results produced by the optimizing procedure. The results shows that the procedure is very efficient.