Maintenance Schedules of Mining HEMM Using an Optimization Framework Model

The asset maintenance is structured via three levels of management – “Strategy, Control and Execution” which helps in defining the overall “asset management strategy”. Maintenance policy and strategy form the basis of rolling business plan. The maintenance strategy with long term objectives and vision is well articulated and communicated to the stakeholders. The key value drivers and the measurement programs are structured and put in place. The equipment assets are tracked and managed throughout their entire lifecycle. Asset management defines, controls and measures the maintenance organization structure with roles and responsibilities. The KPI’s are aligned to the roles as per the organizational structure. The execution level is where the actual work is performed, and continuous improvement is planned and performed. The strategic vision of mining operations is to “ensure safety, quality and compliance to maximize production with minimum costs.

2.png

Figure 2. Maintenance management practices

The above Figure 2 describes how the maintenance process is structured in an organization. The maintenance strategy is defined at an organization level and percolated down for the execution of the maintenance activities. The topmost layer of a “Asset Management Strategy” is maintenance strategy, below which we define the structured controls to measure it. Then the maintenance execution structure is defined where the segregation of maintenance process happens. For high level reporting purpose, we have “planned” an “unplanned” maintenance.

The unplanned maintenance is generally of two types corrective and breakdown. Corrective maintenance (CM) is any maintenance that occurs when the system is failed. Some authors refer to corrective maintenance as repair and we will use them interchangeably throughout this paper. According to MIL-STD-721B, corrective maintenance means all actions performed because of failure, to restore an item to a specified condition [12]. Corrective maintenance further can be defined based on some corrective measures which is taken based on insights or which is done or the left obvers jobs either from breakdown or preventive maintenance.

Preventive maintenance can be defined as three types: time based (n days frequency), performance based (running hours, KM travelled) or imperfect maintenance – the maintenance of deteriorating systems as it will be not as good as new, but younger [13].

Predictive Maintenance is performed as two sub types – CBM (Condition Based Maintenance) and RCM (Reliability Centric Maintenance) [14]. CBM is derived from the insights of condition monitoring of the equipment and their assemblies and based on analysis taking corrective measures to restore to the normal condition [15]. The conditions monitored are thermal, vibration, lubrication and further can be any of operating condition parameters which are non-destructive in nature. RCM – the term reliability centric maintenance refers to a scheduled-maintenance program designed to realize the inherent reliability capabilities of equipment. The Boeing 747 maintenance program so developed was the first attempt to apply reliability centred maintenance concepts. [9]

The TPM (Total Productive Maintenance) is a collaborative approach for continuous improvement on product quality, operational effectiveness, grasp of productivity and safety between organization functions, especially between productivity and maintenance, also emphasize that the “Total” in “TPM” means overall employee involvement in enterprises, i.e. continuous improvement on overall efficiency and active employee involvement [16].

The Figure 4 depicts the timelines of the maintenance schedules as per the system output for execution of maintenance. As shown, the preventive maintenance needs to be performed at a specific frequency say every 3 months, condition-based maintenance is variable and demonstrated here as every 6 months and then after 8 months. Similarly, maintenance schedule generated based on judgment and based on component life cycle also forms an input for the development of the overall maintenance schedule.

3.jpg

Figure 3. Maintenance frequencies based on factors

Figure 3 presents the current situation, where the maintenance team or department has individual maintenance inputs for individual equipment. As presented in Figure 2, the total maintenance is classified into planned and unplanned. The planned maintenance include, the schedules recommended by OEM is generally based on schedule or time based as shown as yellow stars in Figure 3, the RCM provides schedules based on wear and tear or condition monitoring shown as blue stars, judgmental inputs based on experienced manpower insights and inputs which is depicted as green stars and OEM recommended life cycle of an asset component like engine, transmission, tires after certain running hours which is shown as red stars. Further, the unplanned maintenance includes breakdown and corrective maintenance shown as dark blue and brown stars respectively [17]. As observed from Figure 3, the unplanned and planned maintenance time zones do overlap in some cases. These overlapping cases can be optimised by combining the planned maintenance with the unplanned maintenance. With these combinations the maintenance time can be minimised so that the overall availability of the equipment increases. To measure the performance of these combined maintenance activities two new KPIs have been introduced.

The maintenance optimization framework can help resolve the complexity of analysing maintenance schedule plans and provide a decision framework for analysis and automated decision making to minimise the HEMM maintenance time. The optimization framework focuses on production and also helps in increasing safety through the good health of the assets and resources that will also reduce the maintenance cost in the long run. Maintenance scheduling is a complex process which is dependent on multiple factors. To optimise the maintenance scheduling, it is imperative to identify the key factors influencing the maintenance scheduling.

4.1 Influencing factors identification

Some of the key factors which influence in determination of maintenance schedule are:

•        Safety Concern – If the HEMM is not in a safe operating condition at any specific time, maintenance action should be immediate even if scheduled maintenance is planned in near future.

•        Reliability Centric Maintenance (RCM) - The input from RCM is an important parameter to be considered which will recommend an early or later maintenance schedule based on wear and tear analysis or status based on condition of the critical components.

•        Installation and Commissioning - The parameters and performance during the installation and commissioning also have an impact on the performance of asset during its entire useful life cycle.

•        Original Equipment Manufacturer (OEM) Recommendation – The OEM recommends frequencies for preventive maintenance based on elapsed time and/or performance of the equipment as well as schedules for replacement of spare parts. Some of the equipment now comes fitted with monitoring equipment so input of those monitored parameters need to be considered.

•        Failure Analysis Reporting – Failure mode and effect analysis of any component, or chronic failures of the equipment or any critical component need to be provided as inputs to maintenance schedules.

•        Resource Availability (Resource, Manpower) – Workshop capacity and manpower to perform the job should be included in the development of maintenance schedules

•        Weather Forecast – Fog and rain can influence the maintenance of the equipment depending on where the maintenance will be undertaken.

•        Asset Component Life-cycle - Asset life cycle as per OEM manual.

•        Production Schedule and Plan – Production schedules emanating from the system as per the excavation/beneficiation plan.

•        Judgmental – By experience and by observing some key attributes of malfunction.

•        Production Loss – Production loss should be minimized

•        Statutory Body Inspection / Recommendation – External body comments to act upon immediately or within a specified time

•        Subcontractor Availability Including OEM Service – The service which is provided by the subcontractor, their capacity, availability and if any specific skill is required to provide the service.

•        Mean Time between Failures – The MTBF time will also help in decision making for the calculation of schedules for individual HEMM.

•        Spares Availability – Spares availability in the local or central workshop or the lead time to procure the same.

•        Incident/Accident – If any incident or accident has occurred and input for rectifying the HEMM has been suggested by the inspecting authorities.

•        Previous Preventive Maintenance Confirmation – when was the last preventive maintenance was performed and closed.

•        Operating Conditions – Every mine/site has unique terrain; operating condition and each HEMM works in various operating conditions.

The factors were identified, and weightages may be assigned to each influencing factor as per the local strategy of the mine management. Some of these weightages, such as safety, production loss, maintenance spares costs, were converted to costs for optimization, depending on their relative importance. A sample weightage assignment for a specific HEMM type is presented in Table 1 below.

Table 1. A sample of weightages assigned to the key influencing factors

4.2 Model framework

The framework model can be applied both at planning stage as well as at execution stage in maintenance. The general preventive maintenance concept is as per the OEM (Original Equipment Manufacturer) standard operating procedures on time or performance or component replacement date which is linear on a time scale. The preventive maintenance dates will not be exact time based or performance based but each schedule will have dynamic dates considering every attribute as per the weightages assigned to influencing factors (As presented in sample Table 1). The weightage can be variable as per the asset class/HEMM type and the operating region as the same HEMM operating in dusty region or steep gradient requires more frequent maintenance. Another important aspect to be considered during the preventive maintenance is part replacement with a repaired part. The reliability of a repaired part is not the same as that of a new one. This will negatively influence the overall reliability of the equipment owing to the negative weightage attributed to the repaired part. Based on the dependency on the influential factors the framework can be designed to optimize the maintenance scheduling. A model framework based on the influential factors tabulated above is shown in Figure 4.

4.png

Figure 4. Optimization framework flow diagram

A model framework shown in Figure 4 depicts the preventive maintenance orders list and additional insights which may influence the preventive maintenance scheduled date. Further, based on the insights preventive maintenance can be combined with breakdown orders and can be attended either on work site or at workshop. Also, the nature of the preventive maintenance job will decide the subsequent course of action as presented in the flow diagram (Figure 4). Such framework would work with the below objectives:

•            Minimize the time the asset is down for service turnaround time – MTPM (Mean Time for Preventive Maintenance)

•            Maximize the availability of HEMM

•            Minimize number of outages

•            Minimize waste of spare parts useful life

•            Balance workload across outages

•            Improve visibility for production planning, resource planning and service parts planning by providing maintenance, resource demand and service parts forecast.

•            Improve collaboration between asset operators, repair shops and spare parts suppliers. The availability of resources for example manpower, spares, workshops, subcontracted or subcontractor availability.

•            The weather forecast inputs considered for maintenance schedules, depending upon the weather if favorable for maintenance or production.

•            Address safety concerns more actively.

•            Increase productivity of mines.

4.3 Mathematical model

The main objective of maintenance framework is to reduce the total maintenance down time and minimize the total maintenance costs. To fulfil the above-mentioned objective, it has been tried to corelate the various influencing parameters (as detailed in section 4.1) by developing a mathematical model.

The following notation is used in the model:

np: number of HEMM in the mine

nc: number of maintenance bay in the maintenance workshop

nd: number of days in the planning horizon.

i: index for HEMM, i = 1; 2; . . . ; np.

j, k: index for maintenance bay; j; k = 1; . . . ; nc.

d: index for days; d = 1; 2; 3; . . . ; nd. nd + 1 = 1, nd +2 = 2, nd + 3 = 3, because of the cyclic schedule. Like the same one day before day d = 1 is nd, and 2 days before the day d =1 is nd - 1.

j(d): workshop bay j on day d

t = index for particular time period

gij: Breakdown Maintenance cost for equipment  i at bay j.

hij: Preventive maintenance cost for equipment i at bay j.

pj: the number of HEMM that can take Maintenance check at bay j.

rijt: cost incurred in marching of HEMM i to workshop j at time period t.

The following decision variables are used in the formulation:

Wij(d) = 1, if HEMM i takes the maintenance check of Breakdown Maintenance at bay j on day d, 0 otherwise.

Zij(d) = 1, if HEMM i takes the maintenance check of Preventive Maintenance at bay j on day d, 0 otherwise.

OTT_(i,j,t) = Transit time onward for equipment e, i for onward journey to workshop and for time period t

RTT_(i,j,t) = Return transit time for HEMM i from workshop bay j.

Yijt = 1, if workshop bay j is available while the maintenance time period t of HEMM i, 0 otherwise.

MCi,t = Maintenance cost for HEMM i, at time period t.

PLi,t = Production loss due to maintenance downtime of HEMM i at time period t

$\begin{aligned} \mathrm{MC}_{\mathrm{i}, \mathrm{t}}=\sum_{i=1, t}^{n_{p}} \sum_{j=1, t}^{n_{c}} \sum_{d=1, t}^{n_{d}} &\left(g_{i j} W_{i j(d)}+\cdot h_{i j} Z_{i j(d)}+\right.\\\left.r_{i j t}\left(O T T_{i j t}+R T T_{i j t}\right)\left(Y_{i j t}\right)\right) \end{aligned}$ (1)

Objective is to minimize the MCi,t;

Subjected to, if the HEMM is not required to be taken to workshop for maintenance then,

$\left(O T T_{i j t}+R T T_{i j t}\right)\left(Y_{i j t}\right)=0$

Subjected to, if workshop bay j is available during a time period t of maintenance of HEMM i,

n_i,t ≤ p_j

The total loss due to maintenance of HEMM can be calculated as:

Total Loss = Production loss during maintenance + Maintenance cost

Or       

 $T L_{i, t}=\sum_{i=1}^{n_{p}} P L_{i, t}+\sum_{i=1}^{n_{p}} M C_{i, t}$    (2)

Optimized planned date of maintenance of HEMM will be the summation of the planned date and schedule change function due to influencing factors and their weightages.  The maintenance dates according to the optimized plan may be preponed or postponed compared to the planned date of preventive maintenance. The schedule change function due to influencing factors is a directly proportional to the conditional as well as the weightages of the influencing factors. The optimized model includes multiple factor (Table 1) which influences the maintenance schedule as per the conditions and are prioritized as per their weightages accordingly the optimized planned date of maintenance is decided.

The following notations are used in the formulation of optimized planned date of maintenance.

JO = Set of Job Orders and jo = 1, 2, …|JO|

S = Required Set of spare part types, and s = 1,2,…|S|.

N(s) = Number of units available of spare part s in the warehouse.

m: manpower personnel,      M= set of [maintenance] personnel, and m=1,2,…|M|

l: shift , L = set of shifts  l = 1, 2, 3, 4 ILI ( 1-shift A, 2- Shift B, 3 – shift C, 4 – General shift)

W(t,l): Weather  attribute   = 0 iff weather is not favorable in period t, and shift l, 1 = otherwise

SAF: Safety attribute = 0 if input influence in not changing the schedule, 1 = otherwise

PDM_i,d,t,l = Planned date of maintenance of HEMM i in period t and day d and shift l.

OPD_i,d,t,l,i = Optimised planned date of maintenance of HEMM i in period t, day d and shift l.

n_i = Influencing factor weightage assigned by the mine management for influencing factor i (i= SAF, W(t,l), N(s) etc.) (0≤n≥1)

If = Influencing factors

SC_i,if (Ion, if)= Schedule change function due to influencing factor impact and their weightages.

$O P D_{i, d, t, l}=P D M_{i, d, t, l}+S C_{i, i f}(\operatorname{lon}, i f)$        (3)

where,

$S C_{i, i f}(\text {Ion, if }) \in W(t, l) * n_{W(t, l)} \cup S A F * n_{S A F}+\ldots .+i f$

$n_{i}$           (4)

The above-mentioned equation can be used for any number of influencing factors depending upon the mine site locations and operating conditions.