Abstract The activity of scheduling the production plan with the aim of achieving an optimal criterion has been explored in literature for several manufacturing sectors, in particular when it comes to solving scheduling NP-complete problems. In Dairy Manufacturing, determining an optimum criterion for the scheduling process has numerous internal and external challenges due to the complexity of this environment. The initial stages in the Dairy process are characterised by a continuous manufacturing environment and specific operational issues are observable: interruptions for the accomplishment of Cleaning-In-Place (CIP); a short raw material lifespan which demands a fast processing rate; and the stochastic raw material supply variation. By highlighting these three aspects, a critical trade-off emerges: CIP cycle-times heavily reduce the processing capacity, whereas the raw material processed requires an increase in available capacity due to the impact of seasonality, perishability and stochastic deliveries. Therefore, the scheduling plan must be dynamically readapted based on the current inventory, volume and frequency supplied, CIP cycle-times, maximum equipment running hours and downstream capacities. The aim of this research is to develop an integrated approach for generating equipment schedules under supply uncertainty typically observed in the dairy sector where criteria of sustainability are effortlessly incorporated for an improved decision-making process. An efficient Multi-objective Algorithm (MOA) combining conflicting key performance metrics such as minimising Work-In-Process (WIP), maximising Service Level Agreement (SLA), Utilisation and Energy consumption is proposed. The novelty consists of the ability to dynamically select trade-off criteria and visualise the optimum production plan according to the conditions defined by the decision-maker. The appropriate schedules are presented in a Pareto Frontier graph highlighting the entire non-dominance region according to the volume and frequency supplied. Even though sustainability metrics are usually ignored during production plan definitions, namely when a weak correlation between both environmental and profitable criteria is identified, the results demonstrate improved performance when both sustainable approaches are well explored.

中文翻译：

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在连续制造过程的动态多目标推荐规划工具中纳入可持续标准：乳制品案例研究

摘要 以实现最优标准为目标的生产计划调度活动已在多个制造部门的文献中进行了探索，特别是在解决调度 NP 完全问题时。在乳制品制造中，由于这种环境的复杂性，确定调度过程的最佳标准具有许多内部和外部挑战。乳制品过程的初始阶段的特点是连续的制造环境和可观察到的特定操作问题：完成就地清洗 (CIP) 的中断；原材料寿命短，需要快速的加工速度；和随机原材料供应变化。通过强调这三个方面，出现了一个关键的权衡：CIP 循环时间大大降低了加工能力，而由于季节性、易腐烂性和随机交付的影响，加工的原材料需要增加可用能力。因此，必须根据当前库存、供应量和频率、CIP 循环时间、最大设备运行时间和下游产能动态调整调度计划。本研究的目的是开发一种综合方法，用于在乳制品行业通常观察到的供应不确定性下生成设备时间表，其中可持续性标准被毫不费力地纳入以改进决策过程。一种高效的多目标算法 (MOA) 结合了相互冲突的关键性能指标，例如最小化在制品 (WIP)、最大化服务水平协议 (SLA)、提出了利用率和能源消耗。新颖性包括根据决策者定义的条件动态选择权衡标准和可视化最佳生产计划的能力。适当的时间表显示在帕累托边界图中，根据提供的数量和频率突出显示整个非优势区域。尽管在定义生产计划时通常会忽略可持续性指标，即当确定环境和盈利标准之间的相关性较弱时，结果表明，当两种可持续方法都得到充分探索时，绩效会有所提高。新颖性包括根据决策者定义的条件动态选择权衡标准和可视化最佳生产计划的能力。适当的时间表显示在帕累托边界图中，根据提供的数量和频率突出显示整个非优势区域。尽管在定义生产计划时通常会忽略可持续性指标，即当确定环境和盈利标准之间的相关性较弱时，结果表明，当两种可持续方法都得到充分探索时，绩效会有所提高。新颖性包括根据决策者定义的条件动态选择权衡标准和可视化最佳生产计划的能力。适当的时间表显示在帕累托边界图中，根据提供的数量和频率突出显示整个非优势区域。尽管在定义生产计划时通常会忽略可持续性指标，即当确定环境和盈利标准之间的相关性较弱时，结果表明，当两种可持续方法都得到充分探索时，绩效会有所提高。