Abstract:
Improper budgeting for material storage, inability to properly determine inventory required and project revenue that can be generated before processing commences have been a plaguing challenge in Cocoa Processing industries. In order to proffer solution to this, an Empirical Model capable of predicting the output yields (the amount of Butter and Cocoa Cake) expected from any known quantity of Cocoa Beans (as input) right from on set before cocoa beans processing activities actually commence was developed. This research identified the parameters needed for processing Cocoa Beans yield; used the identified parameters to develop mathematical models; integrated these models into a unique entity to form logic; developed computer algorithm and software (in two versions) for the developed models. The first version requires two input data: Mass of Cocoa Beans to process and that of foreign materials while the second requires only mass of Cocoa Beans to process as input. The first gives allowance for getting supply of raw materials from different sources of varying quality standards: and the second is more suitable for administrative uses and for sources of known integrity in maintenance of high standard quality of raw material. The developed software was tested and validated for performance evaluation. It was discovered that the software when so run gave successful and promising results; when used in OLAM Cocoa Processing Industry, Akure, Nigeria. A mass of 21500 kg (21.50 Tonnes) Cocoa Beans was brought for processing, the model predicted a yield of 6873.36 kg and 8569.64 kg of Butter and Cake respectively. After processing the 21.50 Tonnes of the available Cocoa Beans the company realized 7005.25 kg and 9130.26kg of butter and cake respectively. The result proved this model to be 95.71 percent efficient
