Scheduling to maximise worker satisfaction and on-time orders

Abstract

Two important managerial objectives incorporated in production planning are the maximisation of the on-time delivery of orders and worker satisfaction. While the maximisation of on-time deliveries has frequently been considered in past production planning research, the component of maximising worker satisfaction has typically been ignored. The assignment of workers to their preferred jobs is an important factor since it results in a productive working environment with high worker performance and a low turnover rate. This study presents a job scheduling model that considers both criteria simultaneously and derives solution approaches to generate non-dominated solutions. The solution approaches are examined under various experimental conditions to evaluate their performance. Finally, a prototype tool developed as a proof of concept is presented. IntroductionThe literature on scheduling problems is vast and diverse given the importance of effectively utilising the limited resources available in manufacturing and service organisations. While the literature has often focused on problems that can be linked to 'machine' type resources, the general framework implies that many problems can also be related to the scheduling of people. For example, the health care sector has adopted techniques applied to manufacturing (including scheduling) to create real value by reducing waste and improving productivity, cost, quality and the timely delivery of patient care services (Johnson, Smith, and Mastro 2012). Worker (staff ) scheduling variables can be very similar to those used to characterise machines. However, a worker's preference/satisfaction in the work they perform does not have such a simple correlation. Preference/satisfaction is not equivalent to the ability or speed of performing a job, although they could be related. In general, workers like to perform jobs they are good/fast at and similarly, dislike jobs they are slow/ inefficient at. However, there are workers that prefer jobs with a high level of complexity or 'nature', even when they may not perform them 'fast/efficiently', and similarly have low preference for another set of jobs they can perform quickly, but find them boring or repetitive.This study addresses an observed problem at a manufacturing facility that produces made-to-order windows and cabinetry. The problem is to find the assignment of jobs to workers that minimises the number of late orders while taking into consideration the preference of the workers (the level of satisfaction of the work assigned to them). The assignment of the preferred jobs to the workers will result in higher morale, higher dedication to work and will reduce company turnover rates. In the setting under consideration, there are multiple pending orders and each order is characterised by a due date, an order type, a processing time and a scheduling time window. Each job (order) consists of only one task and belongs to a job type, while each worker is skilled to perform every job type. Furthermore, each worker has a preference level...

Social Sustainability in Production Planning: A Systematic Literature Review

“…GA [73] j-s (1) GA [74] f-s (1) DMORA [75] f-s (1) MOCGWO [76] j-s (5) GA [77] p-m X -con. [78] p-m X X heuristic [79] p-m X heuristic AP-Affecting Productivity, con.-constraint, DMORA-Discrete Multi-Objective Rider optimization Algorithm, EE-Energy Expenditure, EM-Effect Modeling, EP-Employee Preferences, ER-Ergonomic Risks, f-s-flow shop scheduling, GA-Genetic Algorithm, j-s-job shop scheduling, MOCGWO-Multi-Objective Cellular Grey Wolf Optimizer, p-m-parallel-machine scheduling, s-m-single-machine scheduling, VL-Value Limiting, (1)noise emission, (5)-combined/general assessment methods.…”

“…Refs. [77,78] formulate a multi-objective function to maximize employee satisfaction as well as on-time delivery. Ref.…”

“…Ref. [78] additionally defines a minimum acceptable employee satisfaction. For maximizing the employee satisfaction, a variety score, and minimizing the maximum completion time, [79] introduce a multi-objective function.…”

“…However, within the identified approaches, the DM is not further supported regarding a suitable specification of these parameters and weights. For approaches using an a posteriori method, first, (Pareto) efficient frontiers are identified [62,63,70,[72][73][74][75][76]78,85,97]. Accordingly, a suitable solution can be selected from the set of identified (non-)dominated points to meet the DM's preferences.…”

A multiobjective integrated multiproject scheduling and multiskilled workforce assignment model considering learning effect under uncertainty

“…The results show that the number of workers assigned to each activity may have a positive or negative influence on its processing time. Ruiz‐Torres et al presented a new manpower scheduling model to maximize worker satisfaction. Some heuristic approaches are developed to solve the problem.…”