1. Introduction and Background
Mbeya University of Science and Technology (MUST) is a government-owned university established under
the Universities Act Cap. 346 and the Mbeya University of Science and Technology Charter of 2014. MUST
has over the years developed a distinguished reputation as a centre of excellence in engineering education,
applied research, and professional short-course training in Tanzania. The University's training mandate
extends beyond formal degree programmes to encompass industry-oriented capacity building and workforce
development.
This proposal is submitted by MUST through the Department of Civil Engineering, in close collaboration with
the Department of Mechanical and Industrial Engineering and the Department of Geosciences and Mining
Technology, together with an industry expert from Mbeya Cement Co. Ltd (Amsons Group), in response to
the Request for Quotation/Proposal (RFQ/RFP) issued by Geita Gold Mining Limited (GGML), Project No.
DIR0009412, for the Provision of Maintenance Planning and Scheduling Training.
MUST possesses the requisite academic expertise, practical experience, and institutional infrastructure to
design and deliver a high-quality, industry-relevant training programme tailored to the needs of GGML's
engineering and planning workforce. The proposed team brings together specialists in mechanical
engineering, production systems, mining operations, and industrial management, complemented by over 28
years of hands-on plant operations and maintenance leadership experience from the industry.
This further revised proposal reflects the three-session delivery structure, the revised total of thirty-one (31)
participants, the condensed five-day session schedule, and the change of training venue to Malaika Beach
Resort, Mwanza, all agreed with GGML following further consultation, and the corresponding adjustment to
the total contract value explained in the covering letter and in Sections 3, 4, and 6 below.

2. Understanding of the Assignment
GGML intends to engage an external training service provider to conduct a structured course on Maintenance
Planning and Scheduling for engineering personnel drawn from planning, scheduling, and resourcing
functions. The overarching objective is to improve workforce productivity and quality by eliminating
inefficiencies in maintenance operations through systematic planning, effective coordination of labour, parts,
materials, and equipment access, and disciplined shutdown management.
Our understanding of the assignment, as further revised, is summarised as follows:
● The training targets thirty-one (31) GGML engineering personnel with planning, scheduling, and
resourcing responsibilities, delivered in three (3) sessions of approximately ten to eleven (10–11)
participants each.
● Training will be conducted at Malaika Beach Resort, Mwanza.
● The curriculum must address: (i) fundamentals of maintenance and asset management; (ii)
maintenance planning and performance measurement; (iii) the work planning process; (iv)
scheduling principles and advanced scheduling; (v) shutdown management; (vi) application of
Excel-based tools (Gantt, CPM, PERT, Budget, RCA); and (vii) measurement of maintenance
effectiveness through metrics.
● The service provider is responsible for professional facilitation, training materials, and certificates
of attendance.
● GGML will provide venue arrangements at Malaika Beach Resort, Mwanza, food (lunch), and
transport for the duration of training.
In addition to the prescribed curriculum, MUST proposes to incorporate a practically focused module on the
Application of Artificial Intelligence (AI) Tools in Maintenance Operations, recognising the growing
importance of AI-assisted decision-making in modern maintenance environments. This module will
demonstrate how AI tools can enhance predictive maintenance, work order optimisation, and failure
analysis, without displacing the core technical content required by GGML.

3. Training Approach and Methodology
3.1 Pedagogical Philosophy
MUST adopts a competency-based, experiential learning approach for professional short courses. This
approach recognises that adult learners, particularly experienced engineering professionals, learn most
effectively when training is directly linked to their operational context, grounded in real case studies, and
reinforced through active participation and problem-solving exercises.
The proposed training will integrate:
● Facilitated lectures and structured presentations by expert trainers.
● Group discussions, syndicate work, and peer learning exercises.
● Hands-on Excel-based workshop sessions (Gantt charts, CPM, PERT, Fault Reports, RCA templates,
Budget Tools).
● Case study analyses drawn from the mining, cement, and process industries.
● Practical demonstrations and role-plays for shutdown planning and scheduling scenarios.
● Application exercises using AI-assisted maintenance tools (overview and demonstration level).

3.2 Training Delivery Mode (Further Revised)
As agreed with GGML, the training venue is revised from the GGML premises in Geita to Malaika Beach
Resort, Mwanza. The thirty-one (31) participants will be trained in three (3) sequential sessions of
approximately ten to eleven (10–11) participants each.
Each session will undergo five (5) working days of training (Monday–Friday), condensed from the six (6)
working days set out in Revision 1 while retaining full coverage of the prescribed curriculum content per
session, through consolidation of the Failure Analysis/Budgeting and Predictive Maintenance/AI/Capstone
content into a single extended final day. This results in a total of fifteen (15) training days (3 sessions × 5
days), delivered across three consecutive weeks commencing Monday, 31st August 2026, as set out in the
Revised Master Weekly Training Schedule at Section 4.
Because the three sessions are delivered sequentially, the MUST training team will remain on site at Malaika
Beach Resort, Mwanza for the full engagement, an estimated twenty (20) days in total, inclusive of
mobilisation and the intervening weekend rest days between successive sessions, running from Monday,
12 October 2026 to Friday, 30th October 2026.